Report - The Optimal MSVS Fleet for First-Line Replenishment

Défense

nationale

National

Defence

Defence R&D CanadaCentre for Operational Research and Analysis

Materiel Group Operational ResearchAssistant Deputy Minister (Materiel)

DRDC CORA TR 2006–026December 2006

The Optimal MSVS Fleet for First-LineReplenishment

Bohdan L. KaluznyAdrian J. ErkelensMateriel Group Operational Research

The Optimal MSVS Fleet for First-Line Replenishment

Bohdan L. KaluznyAdrian J. ErkelensMateriel Group Operational Research

Defence R&D Canada – CORATechnical Report

DRDC CORA TR 2006–026

December 2006

Principal Author

Original signed by Bohdan L. Kaluzny

Bohdan L. Kaluzny

Approved by

Original signed by P. Comeau

P. ComeauSection Head (Joint and Common OR)

Approved for release by

Original signed by R. G. Dickinson

R. G. DickinsonDirector Joint and Strategic Analysis

The information contained herein has been derived and determined through best practice and adher-ence to the highest levels of ethical, scientific and engineering investigative principles. The reportedresults, their interpretation, and any opinions expressed therein, remain those of the authors and donot represent, or otherwise reflect, any official opinion or position of DND or the Government ofCanada.

c© Her Majesty the Queen in Right of Canada as represented by the Minister of National Defence,2006

c© Sa Majesté la Reine (en droit du Canada), telle que représentée par le ministre de la Défensenationale, 2006

Abstract

The Medium Support Vehicle System (MSVS) Project will purchase 1,500 standard military pat-tern (SMP) vehicles to support deployable units. One of the tasks of the SMP MSVS variants, a4.5 ton cargo vehicle and an 8 ton Load Handling System (LHS), will be to transport the stores andequipment necessary to support deployed forces. This study determined the daily stores required bya model organization, computed the minimal number of vehicles required to resupply the unit usingvarious fleet configurations, analyzed the replenishment cycle for these configurations under cen-tralized and decentralized scenarios, and recommended an optimal mix of MSVS LHS and Cargovariants.

Résumé

Le projet de système de véhicule de soutien moyen (SVSM) fera l’acquisition de 1 500 véhiculesd’un modèle militaire normalisé pour appuyer des unités déployables. L’une des tâches des variantesdes ces véhicules, un transport d’une capacité de 4,5 tonnes, et un véhicule muni d’un système dechargement de 8 tonnes, consistera à transporter les fournitures et le matériel nécessaires au soutiendes forces déployées. La présente étude a déterminé les fournitures quotidiennes requises par uneorganisation modèle, calculé le nombre minimum de véhicules nécessaires pour ravitailler l’unitéen question en ayant recours à diverses compositions du parc de véhicules, analysé le cycle deravitaillement pour ces compositions dans des scénarios d’unités centralisées et décentralisées ; ellea enfin recommandé une composition optimale de variantes de SVSM avec système de chargementet de variantes de transport.

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ii DRDC CORA TR 2006–026

Executive summary


Bohdan L. Kaluzny, Adrian J. Erkelens; DRDC CORA TR 2006–026; Defence R&DCanada – CORA; December 2006.

Background: As part of a major crown project, the Medium Support Vehicle System (MSVS)Project will purchase two variants of the standard military pattern (SMP) vehicle; a 4.5 ton cargovehicle with a 20′ bed, and an 8 ton Load Handling System (LHS) capable of lifting and carrying20′ containers or quadcons as twenty foot equivalent units. One of the roles of the MSVS will be totransport the stores and equipment necessary to support deployed forces.

Scope: In support to the Project Director MSVS Project, Directorate Material Group OperationalResearch (DMGOR) developed a methodology to determine the optimal mix of MSVS variantsrequired for the replenishment of first line units. The study consists of four steps:

1. Calculating the daily lift requirement to sustain a deployed task force.

2. Computing the minimum number of vehicles needed to transport the lift requirement usingan integer linear program.

3. Analyzing the effects of various fleet mixes, the use of trailers and quadcons and the geo-graphical deployment of the unit on replenishment operations using a simulation model.

4. Recommendation of an optimal fleet (mix of vehicles) that minimizes the logistics footprintof deployed combat service support units while maximizing the efficiency of replenishmentoperations.

The following six fleet configurations were examined:

1. MSVS LHS vehicles (transporting 20′ containers);

2. MSVS LHS and MSVS Cargo vehicles;

3. MSVS LHS and MSVS Cargo vehicles with respective trailers;

4. MSVS LHS and MSVS Cargo vehicles transporting 20′ containers or quadcons;

5. MSVS LHS and MSVS Cargo vehicles with respective trailers, transporting 20′ containers orquadcons; and

6. MSVS LHS and MSVS Cargo vehicles with respective trailers, Heavy Logistic Vehicle Wheeled(HLVW) Palletized Loading System (PLS), HLVW Cargo, using 20′ containers or quadcons.

Principal Results: The optimal mix between MSVS LHS and Cargo variants, being the lightestfleet that minimizes the number of prime movers, depends on the deployment concept. A 40/60split of Cargo/LHS is optimal for decentralized replenishment while 25% of the fleet can be Cargovariants if the supported unit is centralized at one location. A total MSVS LHS fleet is optimal if

DRDC CORA TR 2006–026 iii

the Heavy Logistics Vehicle Wheeled (HLVW) is not utilized to transport the heavier commodities.While trailers can reduce the number of prime movers by up to 50%, they can increase the durationof the replenishment cycle by up to 50%. Using quadcons can reduce the requirement for primemovers by 10% regardless of replenishment scenario.

Future Work: While the final results presented in this report are specific to the model task forcechosen, the vehicles considered, and replenishment cycle assumptions, the optimization and simu-lation models were built to be generic to accommodate future (specialized) studies on optimal fleetmixes.

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Sommaire


Bohdan L. Kaluzny, Adrian J. Erkelens ; DRDC CORA TR 2006–026 ; R & D pour ladéfense Canada – CARO ; décembre 2006.

Explication : Dans le cadre d’un projet important de l’État, le projet de système de véhicule desoutien moyen (SVSM) fera l’acquisition de deux variantes d’un véhicule de modèle militaire nor-malisé : un véhicule de transport d’une capacité de 4,5 tonnes muni d’un châssis de 20 pi, et unvéhicule muni d’un système de chargement d’une capacité de 8 tonnes capable de soulever et detransporter des conteneurs de 20 pi ou des mini-conteneurs Quadcon équivalant à des conteneurs de20 pi. L’un des rôles du SVSM consistera à transporter les fournitures et le matériel nécessaires àl’appui de forces déployées.

Portée : En appui du projet SVSM du directeur de projet, le Directeur - Recherche opérationnelle(Groupe des matériels) (DROGM) a développé une méthodologie pour déterminer la compositionoptimale des variantes de SVSM nécessaires au ravitaillement des unités de première ligne. Cetteétude se compose de quatre étapes :

1. Calcul des besoins de transport quotidien pour soutenir une force opérationnelle déployée.

2. Calcul du nombre minimum de véhicules nécessaires pour transporter le matériel requis àl’aide d’un programme linéaire à nombres entiers relatifs.

3. Analyse des effets de diverses compositions du parc de véhicules, de l’utilisation de re-morques et de mini-conteneurs Quadcon, ainsi que le déploiement géographique de l’unitélors d’opérations de ravitaillement à l’aide d’un modèle de simulation.

4. Recommandation d’une composition optimale du parc de véhicules, ce qui minimise l’espacelogistique des unités de services de soutien au combat tout en maximisant l’efficacité desopérations de ravitaillement.

Les six compositions du parc de véhicules suivantes ont été examinées :

1. SVSM avec système de chargement (qui transportent des conteneurs de 20 pi) ;

2. SVSM avec système de chargement et des variantes de transport ;

3. SVSM avec système de chargement et des variantes de transport avec les remorques ;

4. SVSM avec système de chargement et des variantes de transport qui transportent des conte-neurs de 20 pi ou des mini-conteneurs Quadcon ;

5. SVSM avec système de chargement et des variantes de transport avec les remorques, transportdes conteneurs de 20 pi ou des mini-conteneurs Quadcon ; et

6. SVSM avec système de chargement et des variantes de transport avec les remorques, véhi-cules logistique lourd à roues (VLLR) avec système de chargement palettisé (SCP), VLLRde transport, transport des conteneurs de 20 pi ou des mini-conteneurs Quadcon.

DRDC CORA TR 2006–026 v

Principaux Résultats : La composition optimale des variantes SVSM avec système de chargementet des variantes de transport pour constituer le parc le plus léger minimisant le nombre de véhiculestracteurs dépend du concept de déploiement. Une composition 40/60 de véhicules de transport/àsystème de chargement est optimale pour un ravitaillement décentralisé tandis que 25% du parc devéhicules peut se composer de variantes de transport si l’unité à appuyer est centralisée en un seulendroit. Un parc consistant totalement en véhicules SVSM à système de chargement est optimal sile véhicule logistique lourd à roues (VLLR) n’est pas utilisé pour transporter les chargements pluslourds. Bien que les remorques puissent réduire le nombre de véhicules tracteurs jusqu’à 50%, ilspeuvent accroître la durée du cycle de ravitaillement jusqu’à 50%. L’utilisation de mini-conteneursQuadcon peut réduire le besoin en véhicules tracteurs de 10%, quel que soit le scénario de ravi-taillement.

Travaux Futurs : Tandis que les résultats finals présentés dans ce rapport sont spécifiques à l’orga-nisation modèle choisie, les véhicules considérés, et des prétentions d’opérations de ravitaillement,les modèles d’optimisation et de simulation sont génériques et peuvent être adapter pour d’autresétudes (spécialisées) des compositions du parc de véhicules.

vi DRDC CORA TR 2006–026

Table of contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Résumé . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i

Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Sommaire . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Table of contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii

List of tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix

List of figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . x

Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi

1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1 Scope . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.1 Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

2.2 Containers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.3 Cargo Compatibility Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . 3

2.4 Forward Resupply . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

3 Scenario Model and Resupply Requirements . . . . . . . . . . . . . . . . . . . . . . . . 5

3.1 Organization and Scenarios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

3.2 Supply Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

4 Minimizing the Number of Vehicles . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.1 Optimization Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

4.2 Overview of Centralized Scenario Results . . . . . . . . . . . . . . . . . . . . . 11

4.3 Overview of Decentralized Scenario Results . . . . . . . . . . . . . . . . . . . . 13

4.4 MSVS Substitution for HLVW . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

4.5 Number of Cargo Vehicles in MSVS Fleet . . . . . . . . . . . . . . . . . . . . . 15

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4.6 The Effect of Quadcons . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.7 The Effect of Trailers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.8 Sensitivity Analysis of Ammunition Requirements . . . . . . . . . . . . . . . . . 17

5 Analysis of Replenishment Operations . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

5.1 Simulation Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

5.2 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

6 The Optimal Mix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

6.1 Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

6.2 Ranking of Fleet Mixes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33

Annex A: Consumption Rates and Lift Requirements . . . . . . . . . . . . . . . . . . . . 35

Annex B: Ammunition Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37

Annex C: ILP Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

C.1 Sets . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

C.2 Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45

C.3 Main Decision Variables . . . . . . . . . . . . . . . . . . . . . . . . . . 45

C.4 Objective Function . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

C.5 Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

Annex D: Centralized Optimization Results . . . . . . . . . . . . . . . . . . . . . . . . . 51

Annex E: Decentralized Optimization Results . . . . . . . . . . . . . . . . . . . . . . . . 59

Annex F: Simulation Statistics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

List of symbols/abbreviations/acronyms/initialisms . . . . . . . . . . . . . . . . . . . . . . 69

Distribution letter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71

viii DRDC CORA TR 2006–026

List of tables

Table 1: Vehicles and Trailers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Table 2: Shipping Container Characteristics . . . . . . . . . . . . . . . . . . . . . . . . 3

Table 3: Model Organization Unit Structure . . . . . . . . . . . . . . . . . . . . . . . . 5

Table 4: Decentralized Scenario: Sub-unit Locations . . . . . . . . . . . . . . . . . . . 6

Table 5: Supply Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Table 6: Calculated Centralized Lift Requirement . . . . . . . . . . . . . . . . . . . . . 8

Table 7: Calculated Decentralized Lift Requirement . . . . . . . . . . . . . . . . . . . 8

Table 8: Vehicle and Trailer Requirements for Centralized Replenishment . . . . . . . . 12

Table 9: Vehicle and Trailer Requirements for Decentralized Replenishment . . . . . . . 13

Table 10: The Effect of Quadcons in Centralized Replenishment . . . . . . . . . . . . . . 16

Table 11: The Effect of Quadcons in Decentralized Replenishment . . . . . . . . . . . . 16

Table 12: Vehicle Load Times (minutes) . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Table 13: Distribution of Load and Unload Resources for Decentralized Scenarios . . . . 20

Table 14: Vehicle Unload Times (minutes) . . . . . . . . . . . . . . . . . . . . . . . . . 22

Table 15: Replenishment Cycle Duration (hrs) for Fleet Mixes . . . . . . . . . . . . . . . 24

Table 16: Probability of Breakdown for Different Fleet Mixes . . . . . . . . . . . . . . . 26

Table 17: Scoring Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

Table 18: Rating of Fleet Mixes for Centralized Replenishment Operations . . . . . . . . 28

Table 19: Rating of Fleet Mixes for Decentralized Replenishment Operations . . . . . . . 29

Table 20: Percentage of MSVS Variants in Top Ranked Fleet Mixes . . . . . . . . . . . . 29

Table A.1: Task Force Daily Consumption (kg/day) (Less Ammunition) . . . . . . . . . . 35

Table A.2: Task Force Daily Lift Requirement (Standard NATO Pallets) (Less Ammunition) 36

Table C.1: Sets Used in ILP Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . 46

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Table C.2: Payload Capacity Minus Container Weight . . . . . . . . . . . . . . . . . . . . 46

Table F.1: RP Load Times (hrs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Table F.2: Convoy Duration for Different Fleets (hrs) . . . . . . . . . . . . . . . . . . . . 66

Table F.3: Unload and Load at Camp Time (hrs) . . . . . . . . . . . . . . . . . . . . . . 67

Table F.4: Unload at RP Time (hrs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

List of figures

Figure 1: Load Handling System (LHS) Unloading ISO Container . . . . . . . . . . . . 2

Figure 2: Four Quadcons form a TEU . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Figure 3: Prime Movers Required for Centralized Replenishment . . . . . . . . . . . . . 14

Figure 4: Prime Movers Required for Decentralized Replenishment . . . . . . . . . . . 15

Figure 5: Sensitivity to Ammunition Usage Rate: % LHS vs. % Cargo . . . . . . . . . . 18

Figure 6: Average Replenishment Cycle Time (hrs) . . . . . . . . . . . . . . . . . . . . 24

Figure 7: Example of Sensitivity of RP Load Times (hrs) to the Number of Resources . . 25

Figure F.1: RP Loading Times (hrs) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65

Figure F.2: Convoy Duration for Various Fleet Mixes (hrs) . . . . . . . . . . . . . . . . . 66

Figure F.3: Avgerage Unload and Load at Camp Time (hrs) Dominated by Time to LoadContainers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67

Figure F.4: Unload at RP (hrs) for Vehicles Carrying Containers . . . . . . . . . . . . . . 68

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Acknowledgements

The authors would like to aknowledge Maj. B.J. Chapman, Royal Military College, Kingston,Canada, for helpful discussion on modeling lift requirements; and Maj. J.M. Morin and CaptainV. Plourde, Director Land Requirements, Ottawa, Canada, for providing timely feedback and datarequired to model the replenishment cycle.

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1 Introduction

For nearly twenty five years the Canadian Forces (CF) have relied on the Medium Logistic VehicleWheeled (MLVW) for land combat service support functions as the MLVW has the most wide-ranging support and operational tasks of all vehicle fleets [1]. Acquired in 1982, the MLVW isnearing the end of its service-life, due to increased maintenance costs, corrosion, and reduced partavailability [2]. As part of a $1.2 billion project, the Medium Support Vehicle System (MSVS)Project will purchase 1,500 standard military pattern (SMP) vehicles to support deployable units[3]. Two variants of the SMP MSVS will be acquired: a 4.5 ton cargo vehicle with a 20′ bed,and an 8 ton Load Handling System (LHS) capable of lifting and carrying 20′ containers, sets of 4quadcons, or flat racks. One of the roles of the MSVS will be to transport the stores and equipmentnecessary to support deployed forces.

The Project Director of the MSVS Project/Directorate Land Requirement 6 (DLR 6-2) asked the Di-rectorate Material Group Operational Research (DMGOR) to develop a methodology to determinethe optimal mix of SMP MSVS variants required for the resupply of first line units [4]. Furtherbackground discussion is provided in Section 2.

1.1 Scope

The DMGOR response, detailed in this report, was to:

– Determine the daily amount of supplies required by a model organization consisting of a wheeledbattle group sized task force of 1403 personnel split into 11 sub-units.

– Determine the minimum number of vehicles required to resupply the battle group. The study con-siders MSVS variants, Heavy Logistic Vehicle Wheeled (HLVW) variants, trailers, and differenttypes of containers for both centralized scenarios (all sub-units co-located) and decentralizedscenarios (sub-units split among five camps each requiring its own resupply).

– Study the replenishment cycle of different vehicle mixes for both centralized and decentralizedscenarios. Factors such as vehicle and trailer loading and unloading times, vehicle reliability,convoy speeds, and availability of material handling equipment were considered.

– Recommend an optimal fleet of vehicles for centralized and decentralized scenarios.

DMGOR conducted the study in four phases. The daily supply requirement for the modeled taskforce was calculated using standard planning consumption rates and pallet weights for North At-lantic Treaty Organization (NATO) classes of supply. We exhibit the calculations in Section 3. Next,the minimum number of vehicles required to perform the resupply was determined by modeling andsolving an integer linear program (ILP). Multiple fleet configurations were considered. The modeland results are explained in Section 4. The third phase examined the replenishment cycle for var-ious fleet configurations. A simulation model was built to analyze factors such as loading times,reliability, convoy speeds, equipment availability, etc. (Section 5). Finally, multi-criteria decisionanalysis determined the optimal mix of MSVS vehicles required to resupply the battle group. Insection 6 we detail the findings.

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2 Background

Historically the medium lift capability has been filled by a 2.5 ton capacity vehicle, however ad-vances in wheeled vehicle mobility and the ever increasing logistic support requirements of modernforces have led various countries to either increase the carrying capacity of the medium vehiclefleet or procure a mixed payload fleet. A Directorate of Operational Research (Joint) study in 2001[5], recommended that the 2.5 ton vehicle, that has been standard for half a century, be replacedwith a vehicle with a larger payload. Establishing vehicle payload for the resupply of combat armsunits and applying a multi-criteria penalty factor, it was determined that a mixed fleet of 4.5 tonand 7 ton vehicles was optimal. A 4.5 ton truck with capacity to lift 10 standard NATO pallets wasrequired. For ammunition, and other heavy stores, a payload of 7 tons was required as unit echelonvehicles tend to bulk out before weighing out when carrying the unit maintenance load, except forammunition, which weighs out before bulking out.

2.1 Vehicles

The fleet of vehicles considered in this study, namely the future MSVS and the existing HLVWprovide deployable tactical sustainment lift capability. The MSVS vehicles that are considered area generic prototype of potential contenders. The carrying capacity of vehicles and trailers are thosespecified as essential in the MSVS Statement of Requirements (SOR) [1] and are detailed in Table1.

Table 1: Vehicles and TrailersVehicle Type Payload (kg) Volume Towing Capacity (kg)MSVS Cargo 4,500 10 pallets 8,000HLVW Cargo 10,000 10 pallets not consideredMSVS LHS 8,000 20′ ISO 12,000HLVW PLS 16,000 20′ ISO not consideredMSVS Cargo Trailer 5,000 10 pallets towed by MSVS CargoMSVS LHS Trailer 8,000 20′ ISO towed by MSVS LHS

Figure 1: Load Handling System (LHS) Unloading ISO Container

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2.2 Containers

International Standards Organization (ISO) type shipping containers will be used to deliver pre-configured loads directly into a supported unit’s location. Container dimensions and capabilitiescan vary dramatically depending on the manufacturer and the target customer. The shipping con-tainers used in this model are based on generic prototypes of single end-opening containers: ISO 20′

containers and military quadcon containers as described in industry advertisements. The containersconform to ISO specifications as described in [6] which are summarized in Table 2. Four quadconshave to be linked together to form the equivalent footprint of a 20′ ISO container - referred to as atwenty foot equivalent unit (TEU) - in order to be lifted by either the HLVW PLS or MSVS LHSequipment. This is necessary as the load handling system is designed to lift only 20′ containersand their equivalent, such as flat racks and A-frames. The payload of 20′ containers and TEU ofquadcons is effectively limited to the payload limitation of vehicles, 16,000 kilograms (kg) in thecase of the HLVW PLS which has the maximum payload capacity of the vehicles we consider.

Figure 2: Four Quadcons form a TEU

Table 2: Shipping Container Characteristics

Type InternalLength(in)

InternalWidth(in)

InternalHeight(in)

Pallets Payload(kg)

Tare Weight(kg)

20′ Container 230 92 87 20 20,000 2700Quadcon 90 56 87 4 4,280 8004 Quadcons 16 17,120 2400

2.3 Cargo Compatibility Constraints

In addition to the volume and weight limitations for each type of vehicle, trailer and container, thereare carrying limitations based on the nature of the cargo. The Transportation of Dangerous GoodsAct and military regulations place restrictions on mixing classes of dangerous goods while beingtransported. Regulations prevent certain dangerous good classes of supplies from being shippedtogether on the same vehicle regardless of the packaging or containerization employed [7, 8]. Otherclasses may be combined on to one vehicle if they are packaged or containerized in such a manner asto prevent leakage from contaminating non-compatible items. The strictest rules apply to Danger-ous Goods Class 1, Explosives. There are Divisional compatibility regulations that prevent certaintypes of ammunition being mixed in storage and transportation. As a simplifying assumption, it


was assumed that there were only four compatibility groups as described below. This compatibilitysystem is similar to the one used in the Arseneau and Taylor study [5]. Items in different compati-bility groups can be combined on a vehicle or trailer as long as they are in different containers. Thecompatibility groups are:– Rations: fresh rations, Individual Meal Packs (IMP), Meals Ready to Eat (MRE) and water.– Packaged petroleum oils and lubricants (POL).– Ammunition: all types of ammunition. No dangerous goods divisional conflict between various

types of ammunition was modeled.– Mixed stores: all other classes of supply, less those listed above, were grouped together as mixed

stores. Mixed stores consisted of general and technical (G & T) stores, engineering stores, defen-sive stores, medical items, repair parts, amenities, and postal material.

Additional restrictions are placed on the transportation of ammunition. Ammunition is not permittedto be loaded onto trailers; all ammunition has to be transported on vehicles. Vehicles carryingammunition can only be loaded to 80% of their payload limit [9].

Individual quadcons are considered to be separate containers. For example, a single MSVS LHScan transport four quadcons: one with rations, one with POL, one with ammunition, and one withmixed stores.

2.4 Forward Resupply

In the past, unit resupply for land operations was traditionally conducted through the delivery points(DP) system. A DP was conducted under cover of darkness and required the combat service supportunit, second line, to move forward and rendezvous with the transport elements of their supportedunits who moved rearwards. A different location had to be secured for each DP. At the DP, storeswould be cross-loaded by hand from second line transport vehicles to a first line unit’s vehicles.This process was labour and resource intensive as well as time consuming.

The DP system has been replaced by a system of forward delivery where the combat service supportunit delivers stores directly to the supported unit’s location thus eliminating the need to secure a sitefor each DP and the effort of cross-loading stores. Forward delivery also enables loads to be pre-packaged onto pallets or into ISO containers. This leads to a more streamlined resupply systemwhich minimizes the double handling of items.

Forward delivery and the pre-packaging of loads enhance the efficiency of the replenishment sys-tem. Directorate Army Doctrine stated that “Essential to success [of future replenishment opera-tions] will be a balanced combination of technologically advanced containers, container-handlingequipment, and ground delivery platforms [ISO compatible]” [10].


3 Scenario Model and Resupply Requirements3.1 Organization and Scenarios

The model organization provided by the sponsor, Project Director MSVS Project, consists of awheeled battle group sized task force with 1403 personnel. The unit structure consists of 11 sub-units described in Table 3.

Table 3: Model Organization Unit Structure

Sub-unit Number of personnelTask Force Headquarters 173Mechanized Infantry Company 159Light Infantry Company 157Direct Fire Support Squadron 144Engineer Squadron 162Artillery Battery 186Combat Service Support Company 166Armored Recce Troop 90Signal Troop 44LAV Ambulance Platoon 76Chemical Biological RadiationNuclear Platoon

46

Total Establishment 1403

Two replenishment scenarios were modeled. The first scenario is a centralized concept where allsub-units are co-located on one camp. The second consists of the sub-units being dispersed on fivedecentralized camps as specified in Table 4.

3.2 Supply Requirements

We now outline the logic and methodology used to determine the daily supply requirements for firstline units. While a task force may operate in any environment and span the spectrum of operationsfrom humanitarian assistance to war fighting, consumption rates were based on war fighting re-quirements as they would provide the extreme requirement of supplies that have to be lifted. NATOand the CF group material, equipment and supplies are separated into ten classes as described inTable 5. Only dry cargo requirements were included in the calculations of unit supply requirements.Bulk liquid cargo, fuel and water are assumed to be delivered in specialized vehicles and trailersequipped with tanks. Palletized water was included to represent a potential extreme lift require-ment. Class VII stores and major end items are also excluded from this study. Class X supplies andmaterial for non-military programs are carried on a space available basis with no vehicles dedicatedto transporting them [11], they are excluded from this study.

For the purposes of this study, the assumption was made that units would be on a push replenish-ment system. Push replenishment is defined as the automatic issue of stores and supplies based on


Table 4: Decentralized Scenario: Sub-unit LocationsCamp Sub-units Total Camp StrengthCamp 1 Task Force Headquarters

Combat Service Support CoySignals TroopLAV Ambulance PlatoonEngineer Squadron Headquarters andSupport TroopChemical Biological RadiationNuclear Platoon

577

Camp 2 Light Infantry CompanyEngineer Troop 204

Camp 3 Mechanized Infantry CompanyEngineer Troop 202

Camp 4 Direct Fire Support SquadronArmored Recce Platoon 234

Camp 5 Artillery Battery 186

established operational or administrative procedures. Each day, units are issued a pre-configuredamount of stores based on forecasted usage rates as per the Staff Data Handbook (SDH) [12]. Unitsdo not submit requirements for specific items. The weight and volume of stores that needed to belifted were determined by using SDH planning figures. SDH provides standardized usage rates foreach class of supplies. Usage rates are given as kilograms per person per day. SDH also providesstandardized weights per pallet for each class of supply. Some of these values were adjusted in thestudy by Arseneau and Taylor [5] into medium logistic vehicles. The adjusted values were retainedfor this study with the approval of the sponsor. The volume of a commodity required to be liftedeach day, in terms of standard NATO pallets, is calculated as:

# of Pallets =⌈

# of personnel (persons)×usage rate (kg/person/day)weight per pallet (kg/pallet)

⌉. (1)

The values for the daily consumption rate and weight per pallet used in this study are provided inTable 5. The supply requirements for the model organization were calculated for both centralizedand decentralized scenarios, and are presented in Tables 6 and 7. The detailed usage rates and liftrequirement calculations are contained in Annex A for all commodities less ammunition, and inAnnex B for ammunition. The calculation of daily supply requirements determined that the taskforce required a total of 118,894 kg of supplies. This was distributed on 210 standard NATO palletsin the centralized scenario. As all stores were palletized and classes of supplies were not mixed ona pallet, the decentralized scenarios required 231 pallets, a 10% increase in the number of palletsover the centralized scenario.

The ammunition usage of a unit in operations is based on the type and intensity of operations andthe environment in which the unit is operating. War fighting entails significantly higher ammunition


Table 5: Supply Requirements

SupplyClass

Commodity DailyConsumptionRate(kg/soldier/day)

Weight perPallet (kg)

Remarks

I IMP 4.98 698 Assumed that onlyIMP were consumed

I Meals Ready to Eat 2.4 1006I Fresh rations 3.1 350I Water 13.97 900 For personal

consumption onlyII G & T Stores 2.9 300III POL (Packaged) 21.7 425 Bulk POL

not includedIV Engineer Stores

(Construction)6.3 544

IV Defensive Stores(Barrier)

4.3 288

V Ammunition Requirement calculated separatelyVI Personal

Demand Items1.5 150

VII Major End Items not includedVIII Med and Dental Stores 0.76 100IX Repair Parts 0.07 500X Material for

non-military programsnot included

Postal 0.25 100

consumption than peace support or humanitarian operations. War fighting is defined as when aunit is tasked to seek out and engage the enemy. War fighting consumption rates were used asthey represent the extreme requirement that would be placed on the replenishment system. In thedecentralized scenarios a high rate of ammunition was used by all sub-units located at Camps 2, 3, 4,and 5. Sub-units located at Camp 1 were assumed to consume 25% of the war fighting ammunitionusage rate. This is to reflect the high percentage of combat service support and combat supportunits located on Camp 1. In sustainment doctrine, each weapon system is given a basic load ofammunition that is the anticipated usage amount during a period of time. The SDH provides athree-day basic load of ammunition for each type of weapon in terms of rounds per weapon. Thedaily consumption rate of ammunition was taken as one-third of the basic load as given by theSDH. The ammunition requirement was calculated as the sum of the number of weapons of eachtype multiplied by the daily consumption rate. The number of rounds per pallet and weight perpallet for each nature of ammunition was obtained from [13]. The exact number of rounds perpallet and pallet weight for a specific nature of ammunition can vary due to the way it is packedinto cartons and boxes before being palletized. A representative pallet composition was selected for


Table 6: Calculated Centralized Lift Requirement

Class Name Wgt/Pallet # PalletsI IMP 698 11I Water 900 22

III POL Packaged 425 10V Ammunition 755 84IV Engineer Stores

(Construction)544 17

IV Defensive Stores(Barrier)

288 21

II G & T Stores 300 14VI Amenities 150 15IX Repair Parts 500 1

VIII Medical &Dental Stores

100 11

Postal 100 4Total: 210

Table 7: Calculated Decentralized Lift Requirement

Camp 1 Camp 2 Camp 3 Camp 4 Camp 5Name wgt/

plt# plt wgt/

plt# plt wgt/

plt# plt wgt/

plt# plt wgt/

plt# plt

IMP 698 5 698 2 698 2 698 2 698 2Water 900 9 900 4 900 4 900 3 900 3PackagedPOL Products

425 4 425 2 425 2 425 2 425 2

Ammunition 1011 4 539 7 819 10 754 21 755 45Engineer Stores(Construction)

544 7 544 3 544 3 544 3 544 3

Defensive Stores(Barrier)

288 9 288 4 288 4 288 3 288 3

G & T Stores 300 6 300 2 300 2 300 2 300 2Amenities 150 6 150 3 150 3 150 2 150 2Repair Parts 500 1 500 1 500 1 500 1 500 1Medical &Dental Stores

100 5 100 2 100 2 100 2 100 2

Postal 100 2 100 1 100 1 100 1 100 1Total Pallets: = 58 = 31 = 34 = 42 = 66

each nature of ammunition. A simplifying assumption was made that all pallets conformed to thedimensions of a standard NATO pallet. For each sub-unit, fractions of pallets for specific natures of


ammunition were summed to obtain the total number of pallets of ammunition required (see AnnexB). A weighted average of pallets weights was taken as a representative pallet weight.


4 Minimizing the Number of Vehicles

Given the daily resupply requirements, the next phase of the study was to determine the minimumnumber of vehicles that would be required to lift the stores. The HLVW Cargo, HLVW PLS, MSVSCargo, MSVS LHS and associated MSVS trailers were considered as transporters, with the HLVWPLS, MSVS LHS and MSVS LHS trailer capable of carrying 20′ containers or quadcons. Thesponsor requested that multiple configurations were to be analyzed; from a basic fleet consisting ofMSVS LHS vehicles carrying 20′ containers, to an all-inclusive configuration including all trans-porters and container types. In particular, the following six fleet configurations were selected:






6. MSVS LHS and MSVS Cargo vehicles with respective trailers, HLVW PLS, HLVW Cargo,using 20′ containers or quadcons.

4.1 Optimization Model

The optimization problem was modeled mathematically as an integer linear program (ILP): a systemof (decision) variables directed by a linear objective function, constrained by linear inequalities. ILPmodels have been studied extensively 1 and their solvers provide a mechanism of sifting throughmany combinatorial possibilities, such as the ones presented by the vehicle loading problem. TheILP formulation is detailed in Appendix C, however we provide the reader with insight into how theproblem was modeled in the following paragraphs.

Primary variables of the ILP were chosen to represent the number of vehicles, number of trail-ers, number of 20′ containers, and number of quadcons transporting a particular commodity group.Secondary variables represented the number of pallets of a certain commodity to be loaded onto avehicle/trailer/container. The objective function modeled the minimization of the number of vehi-cles, while also minimizing wasted payload capacity of vehicles: it is favourable to use vehicles withlighter payload capacity when possible. The system of linear inequalities modeled the problem con-straints: all pallets must be lifted, the bulk and payload capacities of all vehicles/trailers/containersmust be respected, ammunition cannot be carried on trailers, and vehicles carrying ammunitioncan be maximally loaded to 80% of their payload capacity. The ILP was modeled using ZIMPL[15] which facilitated generation of different fleet configurations. Each configuration specific ILPformulation was then solved using ILOG’s CPLEX 6.01 [16], an industry-leading ILP solver. Thesolution obtained from CPLEX sets the model variables of the ILP at optimality - the absolute min-imum number of vehicles that would be required to lift all supplies under the given assumptions,vehicle mix, and chosen organization.

1. For an introduction to ILP see [14].


The model was built to determine the minimum number of vehicles that could transport the supplies.It does not specify how to load each of the individual transporters. Bulk and payload constraintswere modeled so that the total bulk and total weight of a commodity placed onto transporters of aparticular type averaged out to satisfy the restrictions of individual transporters.

Let us illustrate by examining a sample ILP solution to our model. Consider the centralized scenariorequirements (refer to Table 6) where only MSVS LHS vehicles carrying 20′ containers or quadconsare permissible. The ILP solution to the formulation indicates that the lift can be accomplished using25 MSVS LHS: 10 carrying 20′ containers and 15 carrying quadcons. Of the ten 20′ container-carrying MSVS LHS, six are to carry the 33 pallets of rations. The six 20′ containers, with a totalof bulk capacity of 120 pallets, can clearly fit 33 pallets. However, it is the weight of the 33 palletsof rations, 27,478 kg, that forces the distribution of the pallets across 6 vehicles, whose combinedpayload capacity is 5,300× 6 = 31,800 kg. The remaining four vehicles carrying 20′ containersare designated to carry all pallets of the defensive stores, G & T, amenities, repair parts, medical& dental, postal, and 9 of the 17 engineering store pallets. This represents a total of 75 palletsweighing 19,394 kg being distributed across four vehicles with total bulk capacity of 80 pallets andweight capacity of 21,200 kg.

The example’s solution indicates that the remaining supplies are to be loaded into quadcons. 15MSVS vehicles carry 60 quadcons. At least 2 quadcons are to be used to carry the remaining 8pallets of engineering stores, at least 3 quadcons for the packaged POL, and at least 21 quadconsfor ammunition. In each case the quadcons will bulk out before weighing out. While the minimumnumber of quadcons required in total is 26, the average weight of a TEU (four of these bulked-outquadcons) exceeds the weight capacity of an MSVS LHS. However spreading the supplies over 60quadcons lowers the average weight of a TEU combination loaded onto an MSVS LHS.

As the example illustrates, we note that the optimal solution to the ILP model does not specifyhow to load individual vehicles, rather it describes the number of pallets per commodity that couldfit onto the optimal number of vehicles/trailers. Similarly, the model does not explicitly dictategroupings of four quadcons to link together to form a TEU. The constraint restricting quadcon-carrying vehicles carrying ammunition to be loaded to at most 80% of their payload capacity wasmodeled by restricting each quadcon carrying ammunition to be loaded at 80%. Nonetheless, foreach vehicle mix modeled and examined in this study, all ammunition-carrying vehicles were loadedunder 80% capacity.

The detailed ILP results are presented in Annex D, while Tables 8 and 9, Figures 3 and 4 display theobjective value for the six configurations in question 2. In the remainder of this section, we analyzethe results of the optimization.

4.2 Overview of Centralized Scenario Results

1. MSVS LHS vehicles (transporting 20′ containers): Twenty seven MSVS LHS vehicleswere required, six weighed out vehicles carrying rations, one vehicle comfortably carrying

2. For easier comparison, we list all transporters in Table 8 and 9. The transporters considered in each configurationare in bold font and have an arrow to the right.


Table 8: Vehicle and Trailer Requirements for Centralized Replenishment

MSVS Cargo& trailer

→ MSVS LHS 27& trailer

HLVW CargoHLVW PLSquadcons? No Tot: 27 vehs

→ MSVS Cargo 7& trailer





HLVW CargoHLVW PLS

→ quadcons? Yes Tot: 25 vehs

→ MSVS Cargo 0→ & trailer 0→ MSVS LHS 15→ & trailer 12

HLVW CargoHLVW PLSquadcons? No Tot: 15 vehs, 12 trls


HLVW CargoHLVW PLS

→ quadcons? Yes Tot: 14 vehs, 11 trls→ MSVS Cargo 1→ & trailer 1→ MSVS LHS 3→ & trailer 3→ HLVW Cargo 0→ HLVW PLS 7→ quadcons? Yes Tot: 11 vehs, 4 trls

packaged POL, 15 weighed out (at 80%) vehicles carrying ammunition, 5 weighed out MSVSLHS carrying mixed stores.

2. MSVS LHS and MSVS Cargo vehicles: Once again 27 vehicles accomplish the lift, 20MSVS LHS and 7 MSVS Cargo. The distribution is similar to the previous configuration,except that packed POL has been transferred to a Cargo vehicle to minimize wasted pay-load capacity. For the same reason one LHS and five Cargo vehicles transport rations, andsome of the mixed stores can be transferred to replace an MSVS LHS with a Cargo vehicle.Ammunition, being heavy, remains on 15 MSVS LHS.

3. MSVS LHS, MSVS Cargo vehicles along with respective trailers: The optimal solution forthis configuration just transfers all of the non-ammunition supplies onto MSVS LHS trailers.Fifteen MSVS LHS carrying ammunition pull 12 trailers. No Cargo vehicles are used.

4. MSVS LHS and MSVS Cargo vehicles transporting 20′ containers and quadcons: Usingquadcons, two vehicles can be eliminated (in comparison to the first two configurations) fora total of 25 vehicles. Fifteen MSVS LHS are still required to carry all the ammunition,however using quadcons we can fit some of mixed stores into quadcons to form TEU withammo quadcons which satisfy the payload restrictions of individual MSVS LHS. Six Cargovehicles carry rations and POL, and four 20′ containers carry the remaining rations and mixedstores.

5. MSVS LHS and MSVS Cargo vehicles along with respective trailers, transporting 20′

containers and quadcons: The lift is accomplished using 14 MSVS LHS vehicles carryingquadcons full of ammunition and some mixed stores. The vehicles pull 11 trailers carrying


Table 9: Vehicle and Trailer Requirements for Decentralized Replenishment

MSVS Cargo& trailer








HLVW CargoHLVW PLS

→ quadcons? Yes Tot: 31 vehs


HLVW CargoHLVW PLSquadcons? No Tot: 22 vehs, 15 trls


HLVW CargoHLVW PLS

→ quadcons? Yes Tot: 20 vehs, 14 trls→ MSVS Cargo 4→ & trailer 4→ MSVS LHS 6→ & trailer 6→ HLVW Cargo 0→ HLVW PLS 5→ quadcons? Yes Tot: 15 vehs, 10 trls

20′ containers full of POL, rations, and mixed stores.

6. HLVW PLS, HLVW Cargo, MSVS LHS and MSVS Cargo vehicles with respective trail-ers and carrying 20′ containers or quadcons: Only 11 vehicles are required to transport allstores. The significant change is due to the availability of the HLVW PLS vehicles whoseheavier payload capacity is ideal for carrying the heavy ammunition and ration stores. Sevenof the vehicles are HLVW PLSs, while the remaining four vehicles are MSVS variants thatare used to transport lighter POL pallets and mixed stores.

4.3 Overview of Decentralized Scenario Results

1. MSVS LHS vehicles (transporting 20′ containers): Thirty five MSVS LHS vehicles wererequired. All camps, with exception to Camp 1, required only one vehicle for each of thenon-ammunition commodities. Ammunition requirements for the individual camps were themain difference in the number of vehicles. Camp 1 has a higher demand for rations and mixedstores and requires additional LHS vehicles for transportation.

2. MSVS LHS and MSVS Cargo vehicles: The availability of MSVS Cargo vehicles did notaffect the total number of vehicles; however fifteen Cargo vehicles were used to carry thelighter loads - minimizing wasted payload capacity.

3. MSVS LHS, MSVS Cargo vehicles along with respective trailers: Similarly to the cen-tralized scenario, all of the non-ammunition stores were transferred onto trailers, reducing thenumber of vehicles required to 22 MSVS variants pulling 15 trailers.


27

20 19

15 14

3

7

6

1

7

0

5

10

15

20

25

30

MSVS LHS MSVS LHS andCargo

MSVS LHS andCargo withQuadcons

MSVS LHS andCargo with

Trailers

MSVS LHS andCargo withTrailers andQuadcons

HLVW, MSVS,Trailers andQuadcons

Fleet Mix

Num

ber o

f Veh

icle

s

HLVW PLS

MSVS Cargo

MSVS LHS

Figure 3: Prime Movers Required for Centralized Replenishment

4. MSVS LHS and MSVS Cargo vehicles transporting 20′ containers and quadcons: Em-ploying quadcons allows for three of the camps to reduce the number of vehicles required.Camps 1 and 4 deduct one vehicle, while Camp 5 - which has a minimal lift requirement forPOL and rations - reduces its number of prime movers by two. Camps 2 and 3 are indifferentto using quadcons.

5. MSVS LHS and MSVS Cargo vehicles along with respective trailers, transporting 20′

containers and quadcons: Adding quadcon capability to an MSVS fleet with trailers doesnot affect the number of vehicles and trailers for Camps 2, 3, and 4. At Camp 1, commoditiescan be transfered to quadcons to eliminate one vehicle and trailer. At Camp 5, one less vehicleis required with an additional trailer however. In all, twenty MSVS variants pulling 14 trailersare required.

6. HLVW PLS, HLVW Cargo, MSVS LHS and MSVS Cargo vehicles with respective trail-ers and carrying 20′ containers or quadcons: The extra payload capacities of HLVW PLSshave an impact on the number of vehicles in Camps 3, 4 and 5. Camps 1 and 2 are unaffectedas the number of heavy pallets (ammunition and water) is limited and can be transported onMSVS vehicles. A total of 15 vehicles and 10 trailers can lift the requirements in this case.

4.4 MSVS Substitution for HLVW

Though the MSVS variants have the same cargo space as HLVW variants, they have a significantlylower weight carrying capacity. The MSVS LHS is limited to 8,000 kg compared to 16,000 kg for


35

20

24

13 12

6

15 7

98

4

5

0

5

10

15

20

25

30

35

40




Trailers



Fleet Mix

Num

ber o

f Veh

icle

s

HLVW PLS

MSVS Cargo

MSVS LHS

Figure 4: Prime Movers Required for Decentralized Replenishment

the HLVW PLS, while the MSVS Cargo can carry 4,500 kg compared to 10,000 for the HLVWCargo. A homogeneous fleet of HLVW PLS transporting 20′ ISO containers requires 15 vehicles tolift the task force’s daily supply requirements under a centralized replenishment concept. In this casethe vehicles carrying rations and ammunition will weigh out while vehicles carrying mixed storesbulk out. The POL stores fit easily into a HLVW PLS. To lift the same daily stores requirement withjust MSVS vehicles, 27 are needed. These additional 12 prime-movers represent an 80% increasein vehicles. The additional vehicles are required due to the weight of rations, including water, andammunition. To support the task force in 5 decentralized camps a total of 25 HLVW or 35 MSVSvehicles are required. Substituting MSVS vehicles for HLVW vehicles represents a 40% increasein the number of vehicles.

4.5 Number of Cargo Vehicles in MSVS Fleet

As the MSVS LHS has both a larger payload and volume capacity than the MSVS Cargo variant,the minimal fleet size of a pure MSVS fleet, in terms of number of prime-movers, can always beachieved with a fleet consisting entirely of MSVS LHS. However, in order to have a lighter fleet oftransport vehicles, MSVS Cargo vehicles can substitute for MSVS LHS vehicles on a one for onebasis in some cases. In the centralized replenishment scenario, using only 20′ containers and notrailers, 7 of the 27 (26%) of the MSVS vehicles could be replaced by the smaller cargo variants.Under the decentralized concept 15 of 35 (43%) of the vehicles can be replaced by MSVS Cargo.


4.6 The Effect of Quadcons

Quadcons have two competing effects on the requirement for prime-movers. The decreased cargocapacity (16 pallets of cargo space and 3200 kg tare weight of four quadcons compared to a capacityof 20 pallets and 2700 kg tare weight of the equivalent 20′ container) is offset by the ability of asingle vehicle to transport more than one commodity group. To put the 500 kg weight differenceinto perspective, it is less than the average weight of one pallet, 566 kg. Surprisingly, the resultsshow that the effect of using quadcons is almost equivalent for both centralized and decentralizedscenarios. It was expected that using quadcons for decentralized scenarios would provide substan-tially more savings than for centralized scenarios. However, as seen in Table 10, using quadconsfor centralized replenishment reduces the vehicle requirement by 7% for fleet mixes of just MSVSCargo and LHS vehicles. For decentralized scenarios, the number of prime movers for a fleet of justMSVS Cargo and LHS vehicles dropped from 35 to 31, a 11% decrease. In a fleet of MSVS Cargoand LHS vehicles with trailers, the use of quadcons reduced the number of prime movers from 22to 20, a 9% reduction in the number of vehicles (see Table 11).

Table 10: The Effect of Quadcons in Centralized Replenishment

MSVS LHS & Cargo MSVS LHS, Cargo & Trailerstype Cargo LHS # of

Movers%Cargo

Cargo CargoTrl

LHS LHSTrl

# ofMovers

%Cargo

Only 20′: 7 20 27 26% 0 0 15 12 15 0%Both: 6 19 25 24% 0 0 14 11 14 0%

Difference in # of Prime Movers: 7% Difference in # of Prime Movers: 7%

Table 11: The Effect of Quadcons in Decentralized Replenishment

MSVS LHS & Cargo MSVS LHS, Cargo & Trailerstype Cargo LHS #

Movers%Cargo

Cargo CargoTrl

LHS LHSTrl

#Movers

%Cargo

Only 20′: 15 20 35 43% 9 5 13 10 22 41%Both: 7 24 31 23% 8 5 12 9 20 40%

Difference in # of Prime Movers: 11% Difference in # of Prime Movers: 9%

4.7 The Effect of Trailers

It was anticipated that using trailers would significantly decrease the number of prime-movers andtherefore drivers required to sustain a force and its logistics footprint. For centralized scenarios, thenumber of prime-movers is cut nearly in half when trailers are introduced. However, for decentral-ized scenarios, the effect is slightly less, just over one third of the vehicles can be removed.

Using trailers also changes the optimal mix between the MSVS Cargo and LHS. Since the MSVSLHS has a higher payload capacity than the Cargo, it is more likely to carry ammunition which isheavy in nature. When trailers are introduced, it is often the lighter, non-ammunition, pallets previ-ously loaded on Cargo vehicles that can be transferred to the new trailers, reducing the percentage


of Cargo vehicles.

The lightest and smallest fleet of MSVS prime-movers required to support the task force is achievedby employing both trailers and quadcons. Only 14 MSVS LHS with 11 trailers (no MSVS Cargovariants) are necessary when trailers and quadcons are available in centralized operations. Decen-tralized operations require 20 prime-movers, 8 MSVS Cargo, 5 with trailers, and 12 MSVS LHSwith 9 trailers to support the task force.

4.8 Sensitivity Analysis of Ammunition Requirements

The most significant factor in determining the total number of vehicles required to sustain the taskforce, and distribution of variants within the fleet, is the ammunition lift requirement. Using SDHconsumption rates to represent the high consumption of war fighting operations, the daily lift re-quirement for ammunition was 84 pallets totaling 63,647 kg of cargo. The artillery battery accountsfor 54% of the task force’s ammunition requirement. This rate of ammunition expenditure required27 MSVS vehicles, 7 Cargo and 20 LHS to sustain the force. To study the sensitivity of the ve-hicle distribution to ammunition usage, we analyzed the lift requirement for varying ammunitionusage rates. Figure 5 displays the results for the pure MSVS fleet for centralized replenishment.At mid-intensity operations, 50% of the ammunition requirement, the MSVS vehicle requirementsfall from 27 to 20 with a even split of 10 MSVS LHS and 10 MSVS Cargo. At low-intensity, 10%of the ammunition requirement, the total number of vehicles decreases to 14: 5 MSVS LHS and 9MSVS Cargo. As expected, when the lift requirement for heavy commodities drops, the number ofvehicles with lighter payload capacity used increases.


0%

20%

40%

60%

80%

100%

0 10 20 30 40 50 60 70 80 90 100

% of Ammunition Consumption

LHSCARGO

Figure 5: Sensitivity to Ammunition Usage Rate: % LHS vs. % Cargo


5 Analysis of Replenishment Operations

The third phase of the study analyzed the replenishment cycle, modeled using Arena SimulationSoftware 10.0 [17]. The daily replenishment cycle is outlined below, followed by an explanation indetail.

Step 1: Load vehicles/trailers at replenishment point (RP)

Step 2: Form convoy

Step 3: Road move to unit location(s)

Step 4: Unload stores

Step 5: Load retrograde stores and containers

Step 6: Reform convoy for return road move

Step 7: Road move back to RP

Step 8: Unload retrograde stores and containers

5.1 Simulation Model

Step1: Load vehicles/trailers at RP

The replenishment cycle commences when vehicles arrive at the RP. Vehicles and trailers arriveempty and ready to be loaded. Vehicles and trailers are loaded if loading resources are available, orwait in queue until a resource is available. Loading resources consist of forklifts (for cargo vehi-cles/trailers) and maneuvering spaces (for container-carrying vehicles/trailers). Loading resourcesare dedicated to their associated transporters. A forklift can unload pallets from a cargo vehicle, butnot from a container, and a container cannot be unloaded in the area reserved for forklift operation.

The time required to load a vehicle was obtained from 1 Service Battalion [18] and 2 ServiceBattalion Transport Companies [19]. These companies polled personnel with recent operationalexperience to obtain an estimate of the minimum, most likely and maximum time required to loadHLVW PLS and Cargo vehicles with and without their trailers. The average of the two units’estimates, which were very similar, was taken (Table 12).

For cargo vehicles and trailers not loaded to bulk-carrying capacity, the loading time was multipliedby a factor to account for the reduced time to load fewer pallets. Vehicles and trailers were con-solidated into four groups based on the number of pallets actually loaded compared to the vehicle’sbulk-carrying capability. A cargo vehicle loaded between 0% and 25% capacity was assumed totake 25% of the full load time (the values in Table 12 were multiplied by 0.25). Similar scalingwas applied for vehicles loaded 26%−50%, 51%−75% and 76%−100%. For each iteration, the


Table 12: Vehicle Load Times (minutes)

Minimum MostLikely

Maximum

Container onto HLVW PLS 12.5 20 3510 pallets on HLVW Cargo 20 27.5 45Container onto HLVW PLSand a container onto trailer

42.5 55 105

10 pallets on a HLVW Cargoand 10 pallets onto trailer

40 57.5 105

model selected a loading duration from a triangular distribution with the minimum time, most likelytime and the maximum time as parameters. The time to load an MSVS variant was assumed to beequal to the load time for the equivalent HLVW variant.

The number of loading and unloading resources was kept constant throughout all scenarios in orderto allow a common base for comparison. In the centralized scenario, 10 spaces are available formaneuvering container-carrying vehicles, both at the RP and the unit location. One space is requiredto load/unload a vehicle or a vehicle and trailer combination. Five forklifts are available at both theRP and at the unit location. A vehicle and trailer utilizes only one forklift at a time. Table 13displays the distribution of loading and unloading resource for decentralized scenarios.

Table 13: Distribution of Load and Unload Resources for Decentralized ScenariosLocation Maneuvering Spaces Forklifts

RP 10 5Camp 1 5 2Camp 2 2 1Camp 3 2 1Camp 4 2 1Camp 5 5 2

Step 2: Forming the convoy

Once individual vehicles are loaded they wait in queue until the last vehicle is loaded. The convoythen departs with all vehicles required to replenish the unit(s). The packet system of road movementwas not used as a large single group of vehicles is becoming the tactical norm.

Step 3: Road move from RP to unit location(s)

The road move to the unit or sub-unit locations was set at 150 kilometers (km) in all cases. Forall iterations, the move duration was between 1.8 and 2.5 hours (hrs), randomly selected from a


uniform distribution. This represents an average speed that varies between 60 and 80 kilometersper hour (kph). The road move distance and duration were selected by the Directorate of LandRequirements (DLR) [20]. The presence of trailers in a convoy has an effect on the speed that aconvoy can maintain due to the additional weight being pulled by the prime mover and the increaseddifficulty in maneuvering a vehicle that is hauling a trailer. If one or more of the vehicles haul atrailer, the duration of the convoy was increased by a factor between 8 and 10%, randomly selectedfrom a uniform distribution. This represents the convoy having to reduce speed in order to accom-modate the slowest vehicles. If a vehicle suffers a mechanical breakdown during the road move, theconvoy duration increases as the vehicle must be repaired in-situ or connected to another vehicleand towed to the convoy destination. The reliability of HLVW and MSVS vehicles are significantlydifferent. Based on CF data, the HLVW runs 2844 km between hardware failures, while the MSVSis projected to achieve 10,000 km between hardware failures [21]. The probability of an equipmentfailure is determined from the exponential failure distribution 3: given the Mean Distance BetweenFailure (MDBF) of a vehicle, the probability that a vehicle fails in a move of length t is

F(t) = 1− e−t

MDBF , (2)

where R(t) = e−t

MDBF is the reliability of the vehicle. For a 150 km route, an MSVS vehicle (withMDBF of 10,000 km) has a probability of failure of F(150 km) = 0.0149, a 1.49% chance ofbreakdown. A HLVW vehicle (with MDBF of 2844 km) has F(150 km) = 0.0514, a 5.14% chanceof breakdown during the route. The probability that one or more vehicles of a convoy break downduring the road move depends on the number of vehicles of each type. The reliability of a convoyof vehicles is equal to the product of the reliability of individual vehicles. Hence, for a convoy withx MSVS variants and y HLVW variants, the probability of a breakdown during a 150 km route is

1− (e−15010000 )x(e

−1502844 )y. (3)

Trailers are considered to be very mechanically reliable and were given zero probability of break-down. The simulation imposes a delay for mechanical breakdown if the probability of a breakdownis greater than a randomly selected number between 0 and 1. The duration of the delay variesbetween 15 and 60 minutes [20], randomly selected from a uniform distribution.

In a decentralized scenario, all vehicles travel together until the convoy split point. The convoy thenseparates into packets destined for the respective camps. No time delay is incurred at this point.

Step 4: Unload stores

When the convoy or packet arrives at the respective camp, the vehicles immediately commenceunloading. Vehicles are unloaded as forklifts and maneuvering spaces become available. If therequired resource is occupied, then the vehicles wait in a queue until a resource becomes free. Thetime required to unload a vehicle/trailer was taken as the average of the estimates provided by thetwo Service Battalion Transport Companies [19, 18] (Table 14).

3. For information on reliability theory see [22].


Table 14: Vehicle Unload Times (minutes)

Minimum MostLikely

Maximum

Container onto HLVW PLS 10 15 32.510 pallets on HLVW Cargo 20 30 45Container onto HLVW PLSand a container onto trailer

45 60 90

10 pallets on a HLVW Cargoand 10 pallets onto trailer

42.5 60 105

Step 5: Load retrograde stores and containers

Once a vehicle/trailer is unloaded, it is reloaded with palletized retrograde stores or an empty ISOcontainer as applicable. All vehicles carrying ISO containers are loaded with a container to bereturned to the RP. The container may be empty. It was assumed that the amount of palletizedretrograde stores to be returned to the RP is 20% of the total palletized cargo delivered. Cargotransporters are loaded to bulk capacity with palletized retrograde stores. Once all of the unit’sretrograde stores are loaded, the remaining cargo vehicles remain empty after being unloaded. Oncethe unloading/reloading is complete, a one hour delay is imposed on the convoy to simulate the timerequired for refueling, maintenance, driver rest and feeding. The one hour delay is irrespective ofany time spent waiting to be unloaded.

Step 6: Reform convoy for return move

All vehicles wait at their respective camp until the last vehicle has completed the rest and feedingbreak. Vehicles then depart the camp in a single group. In decentralized scenarios, the packetsreform a convoy when the last packet is ready to depart its camp.

Step 7: Return road move from camps to RP

The return road move mirrors the outbound road move with respect to the duration, the effect ofhaving one or more trailers in the convoy and the probability and delay associated with a mechanicalbreakdown.

Step 8: Unloading returning vehicles/trailers at RP

Upon arrival at the RP, containers and pallets are unloaded from the vehicles. As all container-carrying vehicles were loaded with return stores or empty containers at the camp, all must be un-loaded. However, only the cargo vehicles/trailers that were reloaded at the camps need unloading.The replenishment cycle ends when the last vehicle is unloaded.


5.2 Simulation Results

Each of the six different fleet mixes optimized in Section 4 were analyzed. One thousand iterationsof each scenario was run. The following statistics were captured:

– Time to load cargo pallets at RP;– Time to load containers at RP;– Convoy duration;– Time to unload containers at destination and load retrograde containers;– Time to unload cargo pallets at destination and load retrograde cargo pallets;– Return convoy duration back to RP;– Time to unload retrograde containers at RP;– Time to unload retrograde palletized cargo at RP;– Probability of a mechanical breakdown during a convoy; and– Total replenishment cycle duration.

The time required to complete the cycle is the summation of the loading time at RP, the convoyduration to the unit location, time spent at the unit(s), the return convoy duration to the RP andthe time to unload retrograde stores. The total time taken by the various fleets for both centralizedand decentralized scenarios is listed in Table 15. Figure 6 displays the average replenishment cycletimes. Charts and statistics for each of the separate parts of the replenishment cycle are available inAnnex F.

The simulation results point to a pure MSVS fleet of LHS and Cargo vehilces without trailers as theoptimal configuration with respect to minimizing the replenishment cycle duration. The statisticscollected back this claim for both centralized and decentralized scenarios.

The effect of loading resources

The replenishment cycle time is sensitive to the number of forklifts and maneuvering spaces. Theimpact of the number of resources depends on the scenario and fleet composition. In the major-ity of cases, the most predominant factor delaying the replenishment cycle is the waiting time formaneuvering space for loading and unloading containers. For this reason the load times for de-centralized operations is not necessarily longer than for centralized operations, despite requiringmore vehicles. The fleets for the decentralized scenario usually have a better balance of containerand pallet-carrying vehicles/trailers and therefore a better utilization of forklifts and maneuveringspaces. This is demonstrated when comparing the loading times for a fleet of MSVS LHS andCargo vehicles with trailers and quadcons (see Table F.1 in Annex F): the centralized replenishmentrequires 14 LHS vehicles and 11 LHS trailers that take an average of 2 hours to load, while theequivalent configuration for decentralized replenishment employs a fleet of 12 LHS vehicles with 9trailers and 8 Cargo vehicles with 5 trailers, taking 1.64 hours to load.

The impact of changing the number of resources varies depending on the fleet mix. For example,since a fleet with HLVW PLS, MSVS LHS and Cargo vehicles with trailers, 20′ containers andquadcons requires fewer vehicles and trailers than a fleet consisting of just MSVS LHS and Cargo


Table 15: Replenishment Cycle Duration (hrs) for Fleet Mixes

Fleet Mix Central DecentralMSVS Cargo

& trailer→ MSVS LHS avg: 10.19 12.12

& trailer min: 9.11 10.62HLVW Cargo max: 12.03 14.20HLVW PLSquadcons? No

→ MSVS Cargo& trailer

→ MSVS LHS avg: 9.07 10.54& trailer min: 7.68 9.25

HLVW Cargo max: 10.88 12.26HLVW PLSquadcons? No



HLVW Cargo max: 10.50 13.42HLVW PLS

→ quadcons? Yes

Fleet Mix Central Decentral→ MSVS Cargo→ & trailer→ MSVS LHS avg: 14.50 16.32→ & trailer min: 12.82 14.61


→ MSVS Cargo→ & trailer→ MSVS LHS avg: 13.99 12.03→ & trailer min: 12.31 10.53


→ quadcons? Yes→ MSVS Cargo→ & trailer→ MSVS LHS avg: 11.32 12.10→ & trailer min: 9.86 10.79→ HLVW Cargo max: 13.37 14.22→ HLVW PLS→ quadcons? Yes

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0




Trailers



Fleet Mix

Hou

rs

CentralizedDecentralized

Figure 6: Average Replenishment Cycle Time (hrs)


vehicles, 15 to 27, it is less affected by decreasing the number of loading resources. This is depictedin Figure 7.

7.84

8.89 9.07

11.6611.32 11.32

12.0312.39

6.00

8.00

10.00

12.00

14.00

Infinite Resources

12 Spaces 4 Forklifts



Loading Resources

MSVS LHS and Cargowith 20' Containers

HLVW PLS and Cargo,MSVS LHS and Cargo with Trailers with 20'Containers and Quadcons

Hour

s

Figure 7: Example of Sensitivity of RP Load Times (hrs) to the Number of Resources

The effect of trailers

A dominant factor, when comparing the cycle duration of different fleet mixes, is the use of trailers.Adding trailer capability can increase cycle duration by 50%, representing five more hours in somecases. This is partly due to the fact that it takes longer to load containers onto a vehicle and trailerthan onto two vehicles, one after the other: a vehicle hauling a trailer must first unhitch its trailer,then unload the vehicle container, then realign with the trailer to unload the trailer’s container.Also, the lower weight limit on trailers results in more containers being needed which lengthens theloading process. For centralized replenishment, the load times increase from an average of 0.93 to2.15 hours if trailers are included in a fleet mix of MSVS LHS and Cargo vehicles. Decentralizedloading time increases from an average of 0.92 to 2.92 hours when trailers are included in a fleet mixof MSVS LHS and Cargo vehicles. The use of trailers also significantly lengthens the time it takesto unload and reload stores and containers. Including trailers in a fleet of MSVS LHS and Cargovehicles with both 20′ containers and quadcons increases the average unload/reload time from 2.48to 6.08 hours, a 145% increase.

As depicted in Table 16, including trailers in the MSVS LHS and Cargo vehicle fleet reduces theprobability of a failure from 0.32 to 0.21, or 34%, for centralized replenishment and from 0.42 to0.32, or 24%, for the decentralized scenario. However, the increase in reliability is overshadowedby reduced convoy speed. The presence of one or more trailers in the convoy reduces the speed ofthe convoy by between 8 and 10%. The top three fleet mixes with shortest cycle time do not includetrailers.


Table 16: Probability of Breakdown for Different Fleet Mixes

Fleet Composition Centralized DecentralizedMSVS LHS 0.32 0.42MSVS Cargo and MSVS LHS 0.32 0.42MSVS Cargo, MSVS LHSand trailers

0.21 0.32

MSVS Cargo, MSVS LHSand quadcons

0.32 0.40

MSVS Cargo, MSVS LHS,trailers and quadcons

0.20 0.27

MSVS Cargo, MSVS LHS,HLVW Cargo, HLVW PLS,trailers and quadcons

0.35 0.35


6 The Optimal Mix

The optimal fleet configuration to replenish a deployed task force should minimize the number ofvehicles, minimize replenishment cycle time, and have a minimal probability of breakdown.

6.1 Criteria

Number of prime movers

In order to maximize the operational capability of a deployed task force and minimize the timerequired to deploy the task force overseas, the logistics footprint must be kept to the minimumpossible. The logistics footprint consists of all the combat service support personnel, equipment,and supplies required to sustain the task force. Reducing the number of vehicles and drivers is themost effective way to reduce the logistics footprint. Trailers have a significantly smaller impact onthe logistics footprint than prime movers.

Replenishment cycle time

The replenishment cycle is timed from the commencement of loading at the RP until the last vehicleor trailer is unloaded at the RP. The duration of the replenishment cycle is the major factor affectingtransportation operations. Longer replenishment cycles increases the demand on drivers. TransportDirective 309 [23] limits the duty day of drivers to 16 hours - the maximum time allowable tocomplete the replenishment in one day.

Probability of breakdown

The reliability of a vehicle fleet was measured by the probability that there would be a mechanicalfailure during a 150 km convoy to the unit location(s).

Since these are competing objectives, a weighted average of the three criteria was used. Each fleetmix was assigned a rating in each criterion based on a five point scale. The scores are based onrelative performance. The range between the best performance and the least desirable performancewas divided into five sub-ranges for the score. A weighted average was then taken to determine theoptimal fleet mix. The criteria and their weighting, approved by Project Director MSVS Project,are detailed in Table 17.

6.2 Ranking of Fleet Mixes

The raw and weighted average scores for the six fleet mixes are contained in Tables 18 and 19.

For centralized replenishment operations, the optimal fleet mix consists of MSVS LHS and MSVSCargo vehicles with trailers, 20′ containers and quadcons. This fleet mix received maximum points


Table 17: Scoring Criteria

Score # of PrimeMovers

CycleDuration (hrs)

Prob. ofBreakdown

Weight: 5 3 2Best Possible 5 < 15 < 9 < 0.20

Above Average 4 16−20 9−10.5 0.21−0.25Average 3 21−25 10.5−12 0.25−0.30

Below Average 2 26−30 12−13.5 0.31−0.35Least Desirable 1 > 30 > 13.6 > 0.36

for minimizing the number of prime movers and reliability. The second best fleet mix consistedof HLVW PLS, MSVS Cargo and LHS variants, trailers and both 20′ containers and quadcons.While this fleet consists of fewer vehicles than a pure MSVS fleet, the lower reliability of theHLVW makes this a less desirable fleet due to increased frequency of breakdowns. The top two fleetmixes for centralized replenishment are also the top two for decentralized replenishment operations,but in reverse order. The fleet of HLVW and MSVS variants with trailers carrying 20′ containersand quadcons performs better in decentralized operation than a pure MSVS fleet. This is becausethe number of HLVWs make up a smaller portion of the fleet and therefore there is a less drasticdifference in reliability scoring between the two fleets.

Table 18: Rating of Fleet Mixes for Centralized Replenishment Operations

#Pr

ime

Mov

ers

Cyc

leD

urat

ion

Rel

iabi

lity

Raw

Scor

e

Raw

Ran

king

Wei

ghte

dAv

g.Sc

ore

Wei

ghte

dR

anki

ng

Criteria Weight: 5 3 2MSVS LHS 2 3 2 7 6 23 6MSVS Cargo and MSVS LHS 2 4 2 8 5 26 5MSVS Cargo, MSVS LHSand trailers

5 1 4 10 2 36 3


2 5 2 9 4 29 4


5 2 5 12 1 41 1


5 3 2 10 2 38 2

The number of MSVS Cargo variants in the optimal fleets is the maximum possible without increas-


Table 19: Rating of Fleet Mixes for Decentralized Replenishment Operations

#Pr

ime

Mov

ers

Cyc

leD

urat

ion

Rel

iabi

lity

Raw

Scor

e

Raw

Ran

king

Wei

ghte

dAv

g.Sc

ore

Wei

ghte

dR

anki

ng

Criteria Weight: 5 3 2MSVS LHS 1 2 1 4 6 13 5MSVS Cargo and MSVS LHS 1 3 1 5 4 16 4MSVS Cargo, MSVS LHSand trailers

3 1 2 6 3 22 3


1 3 1 5 4 16 4


4 2 3 9 1 32 2


5 2 2 9 1 35 1

ing the total number of prime movers. The distribution between MSVS Cargo and LHS vehicles isdependent on the replenishment scenario and whether HLVW PLS are used to transport stores. Thedistribution between the MSVS variants for the top two ranked fleet mixes are presented in Table20.

Table 20: Percentage of MSVS Variants in Top Ranked Fleet Mixes

Scenario Fleet MSVS Cargo MSVS LHSCentralized HLVW and MSVS variants

with trailers and quadcons25% 75%

Centralized MSVS variantswith trailers and quadcons

0% 100%

Decentralized HLVW and MSVS variantswith trailers and quadcons

40% 60%

Decentralized MSVS variantswith trailers and quadcons

40% 60%

The ranking of the various fleet mixes is not sensitive to criteria weighting. When all criteria aregiven equal weighting, the top two fleets in each scenario remain the same.


7 Conclusion

This study addressed the question of determining the optimal mix of SMP MSVS variants; the 8ton Load Handling System (LHS) and the 4.5 ton Cargo, required for the resupply of first line units.The sponsor selected a 1403 person task force engaged in high intensity war fighting operationsas a representative unit. To represent possible future deployments, two scenarios were studied.First a centralized replenishment concept, where all sub-units were co-located on one camp. Adecentralized concept, were sub-units were dispersed to five separate camps, was also studied.

The optimal mix of MSVS variants was determined via a four phase model.

Phase 1: The weight and volume of the daily stores requirement needed to sustain the task forcewas calculated using Staff Data Handbook consumption rates for the NATO supply classes.

Phase 2: An integer linear program model was solved to compute the minimum number of vehiclesrequired to lift supplies. Various fleet mixes consisting of differing combinations of HLVWand MSVS variants, trailers and container types were considered.

Phase 3: Using the ILP results, the impact on replenishment operations of the different fleet mixeswas analyzed by developing a simulation model.

Phase 4: Multi-criteria decision analysis determined the optimal fleet mix that minimizes the lo-gistics footprint and maximizes the efficiency of replenishment operations based on criteriaevaluation weights provided by the sponsor.

Each phase of the model is highly dependent on the results of the previous phases, especially on thedaily stores requirement calculated in Phase 1.

The vehicles, trailers and containers that were included in this analysis were:

MSVS LHS, MSVS Cargo, HLVW PLS, HLVW Cargo,

MSVS LHS trailer, MSVS Cargo trailer,

20′ ISO container, and quadcons.

The optimization model and simulation model are built to handle any vehicle configuration. Thefollowing six fleet mixes were considered for analysis in particular:

1. MSVS LHS vehicle carrying 20′ ISO containers.

2. MSVS Cargo and MSVS LHS vehicles carrying 20′ ISO containers.

3. MSVS Cargo and MSVS LHS vehicles and their trailers carrying 20′ ISO containers.

4. MSVS Cargo and MSVS LHS vehicles carrying 20′ ISO containers or quadcons.

5. MSVS Cargo and MSVS LHS vehicles and their trailers carrying 20′ ISO containers or quad-cons.

6. HLVW Cargo, HLVW PLS, MSVS Cargo, MSVS LHS vehicles and their trailers, 20′ ISOcontainers or quadcons.


The daily supply requirements were calculated using Staff Data Handbook consumption rates forhigh intensity operations in order to have a worse case scenario. In total, the task force’s dailylift requirement was 118,894 kg. Stores were divided into four compatibility groups based onNATO classes of supply: rations, packaged POL, ammunition, and mixed stores (which consistedof engineer and defensive stores, general and technical stores, amenities, repair parts, medical &dental stores and postal requirements). As all stores were assumed to be palletized, 210 pallets weretransported each day for centralized replenishment operations and 231 pallets when the task forcewas decentralized. Ammunition made up a significant portion of the lift requirement, with 63,647kg on 84 pallets being required each day. The artillery battery required 54% of the ammunition.

The minimal number of vehicles, trailers and containers required to load all stores, while respect-ing the compatibility constraints, varied considerably depending on the fleet mix and replenishmentscenario. The HLVW PLS’s large payload capacity makes it essential to achieving the smallest pos-sible fleet size. For centralized replenishment, the smallest fleet of vehicles was 11 prime movers:7 HLVW PLS, 1 MSVS Cargo and 3 MSVS LHS with a total of 4 trailers and employing both 20′

containers or quadcons. For decentralized replenishment, the minimum number rose to 15 primemovers: 5 HLVW PLS, 6 MSVS LHS, 4 MSVS Cargo and 10 MSVS trailers. The optimizationresults revealed the following notable observations:

– The main factor driving the number of vehicles was the ammunition requirement.– The use of quadcons reduces the number of prime movers by around 10% regardless of the

replenishment scenario.– Using trailers can eliminate the need for about half of the vehicles for centralized replenishment,

however only by about a third in the decentralized scenario.– MSVS Cargo vehicles are utilized more in decentralized scenarios where vehicle payloads are

lighter. The distribution between LHS and Cargo variants is sensitive to the consumption rates ofheavy commodities.

– HLVW Cargo vehicles are not selected in optimal vehicle mixes as their payload and bulk capac-ity is dominated by either MSVS LHS or HLVW Palletized Loading System (PLS) vehicles.

To analyze the effects of the various fleet mixes on replenishment operations, Arena software wasused to build a simulation model of the replenishment cycle. The model consisted of loading ve-hicles and trailers at the replenishment point, conducting the road move to the unit location(s),unloading stores at the destination and reloading return stores, the return road move back to theRP and finally the unloading of vehicles and trailers. To load or unload vehicles and trailers, load-ing resources consisting of a limited number of maneuvering spaces and forklifts. The simulationsrevealed the following notable observations:– A pure MSVS fleet consisting of LHS and Cargo variants without trailers results in the quickest

replenishment cycle time for both centralized and decentralized scenarios.– For centralized replenishment, cycle duration ranged from an average of 8.96 hours for a fleet of

MSVS LHS and Cargo vehicles to 13.99 hours for an MSVS LHS and Cargo fleet with trailers.– For decentralized operations the cycle took between an average of 10.54 hours for an MSVS LHS

and Cargo vehicle fleet to 16.32 hours if trailers were included in the fleet mix.– Despite requiring more vehicles, decentralized operations do not necessarily have a longer cycle

duration than the centralized scenario.– Trailers are the most significant factor affecting the replenishment cycle time. Including trailers


results in a 50% increase in cycle time - over 5 extra hours in some cases.– Trailers increase convoy reliability by at least 20%. (This can be attributed to the assumption

that trailers are mechanically very reliable. Under this assumption, a vehicle and trailer is morereliable than two vehicles.)

To determine the optimal fleet mix, three criteria were used to determine a weighted average score.In descending order of importance they were:

1. Number of prime movers required;

2. Replenishment cycle time; and

3. Probability of breakdown.

The top two ranked fleet mixes were the same for both centralized and decentralized replenishmentoperations. The fleet of MSVS LHS and Cargo with trailers and 20′ containers and quadconsperformed best under centralized replenishment. The fleet of HLVW and MSVS variants (25%Cargo) with trailers, 20′ containers and quadcons was a close second. The top two performing fleetswere in reverse order in the decentralized scenario. Here the maximum percentage of cargo vehicleswas 40%.

The optimal distribution between the MSVS Cargo and LHS variants is dependent on the replen-ishment concept and whether HLVW PLS are used to transport task vehicles. In decentralizedreplenishment, the maximum percentage of MSVS Cargo for replenishment of first line units is40%. Under a centralized replenishment concept, if HLVW PLS vehicles are used as task vehicles,then the maximum percentage of cargo variants in the MSVS fleet should be 25%. If HLVW PLSvehicles are not used, then an all MSVS LHS fleet is optimal.


References

[1] Canadian Department of National Defence (2003), Statement of Operational Requirements00002346 Medium Support Vehicle System.

[2] Desmier, P.E. (2004), Estimating the Reliability of the Medium Logisitics Vehicle Wheeled(MLVW), (Research Note RN 2004/03) ORD, Directorate of Operational Research(Corporate), Ottawa, Canada.

[3] Canada First Defence Procurement - Medium-Sized Logistics Trucks (online),www. f orces.gc.ca/site/newsroom/view_news_e.asp?id = 1961 (Access Date: June 27,2006).

[4] Desmier, P.E. (2005), DMGOR Responses to Call Letter FY 05/06.

[5] Arseneau, L. and Taylor, I. (2001), A Methodology For Determining Cost-Effective LandForce Vehicles, (Technical Report RN 2001/05) Directorate of Operations Research (Joint).

[6] United States Department of Defence (January 1997), JP 4-01.7 Joint Tactics Techniques andProcedures for Use of Intermodal Containers in Joint Operations (online),www.dtic.mil/doctrine/ jel/new_pubs/ jp4_01_7.pd f .

[7] F.T. Bognar, Dangerous Goods Policies, Directorate Supply Chain Operations, E-mail:Transportation of Dangerous Good in Quadcons, 07-21-2006.

[8] Director Ammunition Program Management (2005), C-09-153-001/TS-000, Ammunitionand Explosive Safety Manual Volume 1, Storage and Transportation Edition: BASIC C/WCH 001.

[9] Maj. A.R. Haines, DMGSP, E-mail: Ammunition Transportation, 04-07-2006.

[10] Director Land Strategic Concepts (2003), Future Force Concepts for Future ArmyCapabilities, Chapter 11 (online),armyonline.kingston.mil.ca/LFDT S/143000440015374/FPAC_ENG.PDF .

[11] Maj. Fitzsimmons, J4 Task Force Afghanistan, E-mail: Material for Non-military Programs,Lift Requirements, Fri 04-21-2006.

[12] Department National Defence, Staff Data Handbook, B-GL-303-004/AF-001, Chapter 6.

[13] J4 Ammo (2005), C-74-300-D01/TA-000, Ammunition and Explosives TechnicalInformation Ammunition - Logistical Data.

[14] Wolsey, L.A. (1998), Integer Programming, New York: John Wiley & Sons.

[15] K., Thorsten (2004), Rapid Mathematical Programming, Ph.D. thesis, Technische UniversitätBerlin. ZIB-Report 04-58.

[16] CPLEX Version 6.0, ILOG CPLEX Division, Incline Village, Nevada.htt p : //www.cplex.com/.

[17] Arena Simulation Software 10.0, Rockwell Software Inc.htt p : //www.arenasimulation.com/.

[18] Captain S.J. Brinkema, Transport Company 1 Service Battalion, E-mail: HLVW PLSLoading and Unloading Times, 04-04-2006.

[19] Maj. S.L. Hart, Transport and Administration Company 2 Service Battalion, E-mail: HLVWPLS Loading and Unloading Times, 03-10-2006.


[20] Maj. Morin, Director Land Requirements 6-2, Personal Communication, April 2006.

[21] Maj. Morin, Director Land Requirements 6-2, E-mail: Mean Times Between Failures MSVSStudy, 04-26-2006.

[22] Blischke, W.R. and Murty, D.N.P. (2000), Reliability, Modeling, Prediction, andOptimization, Wiley Series in Probability and Statistics, New York: John Wiley & Sons.

[23] DLBM/TM 5 (2006), Transportion Manual, Directive 309, Control of Drivers’ Hours.


Annex A: Consumption Rates and Lift Requirements

The consumption rates in Table A.1 are based on the Electronic Battle Box [12] usage rates foroperations within a Canadian Mechanized Brigade Group context.

Table A.1: Task Force Daily Consumption (kg/day) (Less Ammunition)

Commodity Centralized DecentralizedNATOSupplyClass

Class Name UsageRates(kg/man/day)

Camp 1 Camp 2 Camp 3 Camp 4 Camp 5

PersonnelStrength:

1403 577 204 202 234 186

I CbtRations

4.98 6986.94 2873.46 1015.92 1005.96 1165.32 926.28

I Water 13.97 19599.91 8060.69 2849.88 2821.94 2598.42 2598.42III POL

Packaged2.8 3928.4 1615.6 571.2 565.6 520.8 520.8

IV Engr Stores(Construction)

6.3 8838.9 3635.1 1285.2 1272.6 1171.8 1171.8

IV Def Stores(Barrier)

4.3 6032.9 2481.1 877.2 868.6 799.8 799.8

II G &T 2.9 4068.7 1673.3 591.6 585.8 539.4 539.4VI Amenities 1.5 2104.5 865.5 306 303 279 279VIII Med &

Dental0.76 1066.28 438.52 155.04 153.52 141.36 141.36

IX Repair Parts 0.07 98.21 40.39 14.28 14.14 13.02 13.02Postal 0.25 350.75 144.25 51 50.5 46.5 46.5

All supplies were palletized in standard NATO pallets. Items were segregated by NATO supplyclasses and could not be mixed on a pallet.


Table A.2: Task Force Daily Lift Requirement (Standard NATO Pallets) (Less Ammunition)

Commodity Centralized DecentralizedNATOSupplyClass

Class Name Weight/pallet(kg)

Camp 1 Camp 2 Camp 3 Camp 4 Camp 5

I CbtRations

698 11 5 2 2 2 2

I Water 900 22 9 4 4 3 3III POL

Packaged425 10 4 2 2 2 2

IV Engr Stores(Construction)

544 17 7 3 3 3 3

IV Def Stores(Barrier)

288 21 9 4 4 3 3

II G & T 300 14 6 2 2 2 2VI Amenities 150 15 6 3 3 2 2VIII Medical &

Dental100 11 5 2 2 2 2

IX Repair Parts 500 1 1 1 1 1 1Postal 100 4 2 1 1 1 1

Total 126 54 24 24 21 21


Annex B: Ammunition Requirements

Ammunition Type AIC Rounds/box Box/pallet Rounds/pallet kg/pallet25 mm HEI A975 30 42 1260 109925 mm APFSDS 0103 30 42 1260 98776mm Smoke Grenade 0303 24 15 360 6357.62 4B1T Linked 0047 880 27 23760 11550.50 Cal A557 200 27 5400 9699 mm A360 2880 24 69120 10765.56 mm Ball 0086 910 72 65520 10955.56 4B1T Linked A064 1600 32 51200 1176M-72 H557 15 3 45 271Carl G HEAT 0636 6 9 54 335Carl G Smk 0636 6 9 54 335Carl G Illum 0636 6 9 54 335Eryx 9815 1 4 4 122ALAAWS Missile 9815 1 4 4 12240 mm Gren HE B546 72 27 1944 71441 mm Gren VT B546 72 27 1944 71460mm mort HE 1031 4 60 240 70160mm Ill 1033 4 64 256 82860mm smole 1045 4 60 240 66881mm mort HE 0584 3 64 192 100481mm smoke 0650 3 54 162 100381mm illum 0651 3 54 162 872 How 105 C444 2 20 40 995155mm propellant 1514 1 20 20 380155 HEDP, ICM D563 8 3 24 1191155 HE D544 8 3 24 1087155 Illum D505 8 3 24 1083155 smoke D506 8 3 24 1086TOW II PB93 1 12 12 531ADATS 9810 1 4 4 680105 Tank APFSDS 0635 2 10 20 680105 HESH 0550 1 16 16 673105 Smoke C512 2 15 30 1010

Ammunition Packing Details

Data Source: Ammunition and Explosives Technical Information Publication, C-74-300-D01/TA-000

AIC is Ammunition Interchangability Code

Weapon

2 x 4 76 mm smoke grenade dischargers C6

co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C8 Eryx HMG

Ammunition HEI APFSDS76 mm Smoke Grenade

7.62 4B1T Linked 7.62 4B1T Linked 9mm

5.56 mm Ball Eryx .50 Cal 60mm HE

WLAV LAV III CP 1 150 180 3 587 587WLAV LAV III ISC(Gun Tractor) 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 4 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 4 3 400MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 6 9Rifle Assault (C7)Rifle Carabine (C8) 84 67GPMG Coax Mtd (C6) 587SRAAWL (M72)SRAAW (M2) Carl GEyrx 4 1ALAWSLMG (C9A1)GPMG Flex (C6) 8 587HMG 50 Cal 400Mortars 60mm 5Mortars 80mmHowitzer 155

750 900 27 7627 2933 54 5600 4 1600 01260 1260 360 51200 51200 69120 65520 4 5400 2401099 987 635 1155 1155 1076 1095 122 969 701

1 1 0 0 0 0 0 1 0 02.973

722.610Aveage Pallet Weight

Armoured Reconnaissance Squadron

Number PalletsTotal Pallets

25 mm M242 Cannon

Total RoundsRounds per Pallet

Kg/pallet


Wea

pons

2 x

4 76

m

m s

mok

e gr

enad

e di

scha

rger

sC

6

co-a

xial

7.6

2 m

mn

& a

nti-

airc

raft

C6

MG

P

isto

lC

7C

9C

arl G

CA

SW

Am

mun

ition

HE

IA

PFS

DS

Sm

oke

Gre

nade

7.62

4B

1T

Link

ed7.

62 4

B1T

Li

nked

9mm

5.56

mm

B

all

5.56

4B

1T

Link

edH

EA

T40

mm

G

ren

HE

.50

Cal

81m

m

HE

81m

m

Sm

oke

81m

m

illum

155m

m

Pro

pelle

nt15

5mm

H

ow H

e15

5mm

H

ow Il

lum

155m

m

How

Sm

oke

155m

m H

ow

DP

ICM

WLA

V L

AV

III

CP

615

018

03

587

587

WLA

V L

AV

III

ISC

(Gun

Tra

ctor

)7

150

180

358

758

7W

LAV

CO

YO

TE R

EC

CE

W/G

RD

MTD

S

UR

VE

ILLA

NC

E S

YS

TEM

150

180

358

758

7W

LAV

CO

YO

TE R

EC

CE

W/M

AS

T M

TD S

UR

VE

ILLA

NC

E S

YS

TEM

150

180

358

758

7W

LAV

CO

YO

TE C

OM

MA

ND

150

180

358

758

7W

LAV

MR

T1

150

180

358

758

7W

LAV

Eng

r Rec

ce15

018

03

587

587

WLA

V L

AV

III

BC

/FO

O/M

FC3

150

180

358

758

7M

AR

V3

400

MM

EV

(AD

ATS

)TU

A (T

OW

II)

MG

S (1

05)

Laun

cher

; Gre

nade

40

mm

(M20

3A1)

430

Pis

tol 9

mm

; Bro

wni

ng13

9R

ifle

Ass

ault

(C7)

162

67R

ifle

Car

abin

e (C

8)G

PM

G C

oax

Mtd

(C6)

587

SR

AA

WL

(M72

)S

RA

AW

(M2)

Car

l G8

1E

yrx

ALA

WS

LMG

(C9A

1)8

500

GP

MG

Fle

x (C

6)4

587

HM

G 5

0 C

al4

400

Mor

tars

60m

mM

orta

rs 8

0mm

340

106

How

itzer

155

668

365

1611

2550

3060

5112

320

9973

117

1080

040

008

120

1600

120

3018

408

216

3096

6612

6012

6036

051

200

5120

069

120

6552

038

400

5419

4454

0019

216

216

220

2424

2424

1099

987

635

1155

1155

1076

1095

1063

335

714

969

1004

1003

874

380

1087

1083

1086

1191

22

00

00

00

00

01

00

209

14

3 44 755

25 m

m M

242

Can

non

Tota

l Pal

lets

Ave

rage

Pal

let W

eigh

t

Art

iller

y B

atte

ry

Tota

l Rou

nds

Rou

nds

per P

alle

tK

g/pa

llet

Num

ber P

alle

ts


Wea

pon

2 x

4 76

mm

sm

oke

gren

ade

disc

harg

ers

C6

co-a

xial

7.6

2 m

mn

& a

nit-

airc

raft

C6

MG

P

isto

lC

7C

9C

arl G

Ery

x

Am

mun

ition

Ty

pe

HE

IA

PFS

DS

76 m

m S

mok

e G

rena

de7.

62 4

B1T

Li

nked

7.62

4B

1T

Link

ed9m

m5.

56 m

m

Bal

l5.

56 4

B1T

Li

nked

HE

AT

Ery

x60

mm

HE

60m

m

Sm

oke

60 m

m

Illum

WLA

V L

AV

III

CP

1415

018

03

587

587

WLA

V L

AV

III

ISC

415

018

03

587

587

WLA

V C

OY

OTE

RE

CC

E W

/GR

D M

TD

SU

RV

EIL

LAN

CE

SY

STE

M15

018

03

587

587

WLA

V C

OY

OTE

RE

CC

E W

/MA

ST

MTD

S

UR

VE

ILLA

NC

E S

YS

TEM

150

180

358

758

7W

LAV

CO

YO

TE C

OM

MA

ND

150

180

358

758

7W

LAV

Eng

r Rec

ce15

018

03

587

587

WLA

V L

AV

III

BC

/FO

O/M

FC15

018

03

587

587

MA

RV

3M

ME

V (A

DA

TS)

TUA

(TO

W II

)M

GS

(105

)La

unch

er; G

rena

de 4

0 m

m (M

203A

1)P

isto

l 9m

m; B

row

ning

389

Rifl

e A

ssau

lt (C

7)12

667

Rifl

e C

arab

ine

(C8)

GP

MG

Coa

x M

td (C

6)58

7S

RA

AW

L (M

72)

SR

AA

W (M

2) C

arl G

21

Eyr

x1

1A

LAW

SLM

G (C

9A1)

950

0G

PM

G F

lex

(C6)

158

7H

MG

50

Cal

Mor

tars

60m

m1

55

8M

orta

rs 8

0mm

How

itzer

155

2700

3240

5411

147

1056

034

284

0045

002

15

58

1260

1260

360

5120

051

200

6912

065

520

3840

054

424

024

025

610

9998

763

511

5511

5510

7610

9510

6333

512

270

166

882

82

30

00

00

00

00

00 6

991

25 m

m M

242

Can

non

Tota

l Pal

lets

Ave

rage

Pal

let W

eigh

t

Task

For

ce H

eadq

uart

ers

Squa

dron

60 m

m M

orta

r

Tota

l Rou

nds

Rou

nds

per P

alle

tK

g/pa

llet

Num

ber P

alle

ts


Weapon C6co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C7 C9 Carl G

Ammunition

7.62 4B1T Linked 7.62 4B1T Linked 9mm 5.56 mm Ball

5.56 4B1T Linked HEAT

WLAV LAV III CP 587 587

WLAV LAV III ISC(Gun Tractor) 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 587 587WLAV COYOTE COMMAND 587 587WLAV MRT 587 587WLAV Engr Recce 587 587WLAV LAV III BC/FOO/MFC 587 587MARVMMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 2 9Rifle Assault (C7) 44 67Rifle Carabine (C8)GPMG Coax Mtd (C6) 587SRAAWL (M72)SRAAW (M2) Carl G 2 1EyrxALAWSLMG (C9A1) 6 500GPMG Flex (C6) 6 587HMG 50 CalMortars 60mmMortars 80mmHowitzer 155

3520 0 18 2933 3000 251200 51200 69120 65520 38400 54

1155 1155 1076 1095 1063 3350 0 0 0 0 0

0979

Number PalletsTotal Pallets

Average Pallet

Chemical Nuclear Radiation Biological Platoon

Kg/pallet


Weapon2 x 4 76 mm smoke grenade dischargers C6

co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C7 C9 Carl G HMG


7.62 4B1T Linked 7.62 4B1T Linked 9mm 5.56 mm Ball

5.56 4B1T Linked HEAT .50 Cal

WLAV LAV III CP 150 180 3 587 587WLAV LAV III ISC(Gun Tractor) 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 3 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 3 400MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 15 9Rifle Assault (C7) 133 67Rifle Carabine (C8)GPMG Coax Mtd (C6) 587SRAAWL (M72)SRAAW (M2) Carl G 4 1EyrxALAWSLMG (C9A1) 15 500GPMG Flex (C6) 12 587HMG 50 Cal 2 400Mortars 60mmMortars 80mmHowitzer 155

450 540 9 8800 1760 135 8867 7500 4 8001260 1260 360 51200 51200 69120 65520 38400 54 54001099 987 635 1155 1155 1076 1095 1063 335 969

0 0 0 0 0 0 0 0 0 01.572

1015.325Total Pallets

Average Pallet

Combat Service Support Company

25 mm M242 Cannon

Kg/pallet


Number Pallets



co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C8 ADATS TOW II



5.56 mm Ball ADATS TOW II

105 MM APFSDS 105 HESH

105 Smoke

WLAV LAV III CP 9 150 180 3 587 587WLAV LAV III ISC 1 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587

WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 4 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587

WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 3MMEV (ADATS) 6 5TUA (TOW II) 4 4MGS (105) 4 12 7 2Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 10 9Rifle Assault (C7)Rifle Carabine (C8) 134 67GPMG Coax Mtd (C6) 587SRAAWL (M72)SRAAW (M2) Carl GEyrxALAWSLMG (C9A1)GPMG Flex (C6) 587HMG 50 CalMortars 60mmMortars 80mmHowitzer 155

2100 2520 42 8213 8213 90 8933 30 16 48 28 81260 1260 360 51,200 51,200 69120 65520 4 12 20 16 301099 987 635 1155 1155 1076 1095 680 531 680 673 1010

1.667 2.000 0.117 0.160 0.160 0.001 0.136 7.500 1.333 2.400 1.750 0.26717.492


Average Pallet

Direct Fire Squadron


Kg/palletNumber Pallets

25 mm M242 Cannon 105mm Gun

Weapon

25 mm M242 Cannon


co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C7 C9



5.56 mm Ball 5.56 4B1T Linked

WLAV LAV III CP 7 150 180 3 587 587WLAV LAV III ISC(Gun Tractor) 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 3MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 5 9Rifle Assault (C7) 44 67Rifle Carabine (C8)GPMG Coax Mtd (C6) 2 587SRAAWL (M72)SRAAW (M2) Carl GEyrxALAWSLMG (C9A1) 8 500GPMG Flex (C6) 4 587HMG 50 CalMortars 60mmMortars 80mmHowitzer 155

1050 1260 21 6453 5280 45 2933 40001260 1260 360 51200 51200 69120 65520 384001099 987 635 1155 1155 1076 1095 1063

1 1 0 0 0 0 0 02

1042

Engineer Sqadron (Minus Field Troops)

Total PalletsAverage Pallets





co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C7 Carl G

Ammunition HEI APFSDS 76 mm Smoke Grenade 7.62 4B1T Linked 7.62 4B1T Linked 9mm 5.56 mm Ball HEAT .50 CalWLAV LAV III CP 2 150 180 3 587 587

WLAV LAV III ISC(Gun Tractor) 4 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 3 400MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 1 9Rifle Assault (C7) 44 67Rifle Carabine (C8)GPMG Coax Mtd (C6) 587SRAAWL (M72)SRAAW (M2) Carl G 2 1EyrxALAWSLMG (C9A1)GPMG Flex (C6) 2 587HMG 50 Cal 2 400Mortars 60mmMortars 80mmHowitzer 155

900 1080 18 4693 3520 9 2933 2 8001260 1260 360 51200 51200 69120 65520 54 54001099 987 635 1155 1155 1076 1095 335 969

1 1 0 0 0 0 0 0 02.012


Average Pallet Weight

25 mm M242 Cannon

Field Troop

Kg/pallet


Number Pallets

Weapon Pistol C7

Ammunition 9mm5.56 mm Ball

WLAV LAV III CPWLAV LAV III ISC(Gun Tractor)

WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM

WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEMWLAV COYOTE COMMANDWLAV MRTWLAV Engr RecceWLAV LAV III BC/FOO/MFCMARVMMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 1 9Rifle Assault (C7) 75 67Rifle Carabine (C8)GPMG Coax Mtd (C6)SRAAWL (M72)SRAAW (M2) Carl GEyrxALAWSLMG (C9A1)GPMG Flex (C6)HMG 50 CalMortars 60mmMortars 80mmHowitzer 155

9 500069120 65520

1076 10950.000 0.076

0.0761094.968

Total PalletsAverage Pallet Weight

Total Rounds

LAV Ambulance Platoon

Rounds per PalletKg/pallet

Number Pallets


Weapon C6 Pistol C7 C9 Carl G Eryx CASWAmmunition 7.62 4B1T 9mm 5.56 mm Ba5.56 4B1T HEAT Eryx 40 mm Gre .50 Cal 60mm HE 60mm Smo60 mm Illum

WLAV LAV III CPWLAV LAV III ISC 587

WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 587

WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 587WLAV COYOTE COMMAND 587WLAV MRT 587WLAV Engr Recce 587WLAV LAV III BC/FOO/MFC 587MARV 400MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1) 5 30Pistol 9mm; Browning 7 9Rifle Assault (C7) 130 67Rifle Carabine (C8)GPMG Coax Mtd (C6)SRAAWL (M72)SRAAW (M2) Carl G 4 1Eyrx 13 1ALAWSLMG (C9A1) 20 500GPMG Flex (C6) 8 587HMG 50 Cal 2 400Mortars 60mm 4 5 5 8Mortars 80mmHowitzer 155

4693 63 8667 10000 4 13 150 800 20 20 3251200 69120 65520 38400 54 4 1944 5400 240 240 256

1155 1076 1095 1063 335 122 714 969 701 668 8280 0 0 0 0 3 0 0 0 0 0

4316Average Pallet Weight

Total Pallets

60 mm MortarLight Infantry Company



Weapon25 mm M242 Cannon


co-axial 7.62 mmn & anit-aircraft C6 MG Pistol C7 C9 Carl G Eryx



5.56 mm Ball

5.56 4B1T Linked HEAT Eryx

WLAV LAV III CP 2 150 180 3 587 587WLAV LAV III ISC 13 150 180 3 587 587WLAV COYOTE RECCE W/GRD MTD SURVEILLANCE SYSTEM 150 180 3 587 587WLAV COYOTE RECCE W/MAST MTD SURVEILLANCE SYSTEM 150 180 3 587 587

WLAV COYOTE COMMAND 150 180 3 587 587WLAV MRT 2 150 180 3 587 587WLAV Engr Recce 150 180 3 587 587

WLAV LAV III BC/FOO/MFC 150 180 3 587 587MARV 3MMEV (ADATS)TUA (TOW II)MGS (105)Launcher; Grenade 40 mm (M203A1)Pistol 9mm; Browning 7 9Rifle Assault (C7) 134 67Rifle Carabine (C8)GPMG Coax Mtd (C6) 7 587SRAAWL (M72)SRAAW (M2) Carl G 4 1Eyrx 9 1ALAWS 0LMG (C9A1) 18 500GPMG Flex (C6) 587HMG 50 CalMortars 60mmMortars 80mmHowitzer 155

2550 3060 51 9973 14080 63 8933 9000 4 91260 1260 360 51,200 51,200 69120 65520 38400 54 41099 987 635 1155 1155 1076 1095 1063 335 1222.024 2.429 0.142 0.195 0.275 0.001 0.136 0.234 0.074 2.250

7.760767.116

Total PalletsAveage Pallet Weight

Mechanized Infantry Company






Annex C: ILP Formulation

We modeled the problem of minimizing the number of prime movers and wasted payload capacity asan integer linear program (ILP). We first define sets and specify the input parameters, then proceedto the model variables, objective function and constraints.

C.1 Sets

Let T = {1, ..,9} be the set of transporters where

1− HLVW Cargo,2−MSVS Cargo,3−MSVS Cargo trailer,4− HLVW PLS carrying a 20′ container,5−MSVS LHS carrying a 20′ container6−MSVS LHS trailer carrying a 20′ container,7− HLVW PLS carrying four quadcons,8−MSVS LHS carrying four quadcons,9−MSVS LHS trailer carrying four quadcons.

We also define the subset Q = {7,8,9} as the set of transporters carrying quadcons, and T RL ={3,6,9} as the set of trailers. Further sets based on the commodities are defined in Table C.1.

C.2 Input Parameters

As input, we are given the pallet weight, wi, and number of pallets to be lifted, li, for each commod-ity i ∈ ALL. We are given the bulk capacity, bi, of each i ∈ T ; cargo transporters can carry up to tenpallets (b1,b2,b3 = 10), up to twenty pallets can be stacked into 20′ containers (b4,b5,b6 = 20), andeach quadcon can carry a maximum of four pallets.

The payload capacity, p̂i, of each transporter i ∈ T is given, from which we calculate the actualpayload capacity, pi, which takes into account the weight of containers (Table C.2). Each quadconweighs 800 lbs and a 20′ container weighs 2700 lbs.

C.3 Main Decision Variables

Define integer variables xi, j to be the number of pallets of commodity j ∈ ALL to be loaded ontotransporter i ∈ T \Q. Define integer variables zi, j to be the number of transporters i ∈ T \Q thatcarry commodities j ∈C.

For transporters carrying quadcons, define integer variables xi, j to be the number of pallets of com-modity j ∈ ALL to be placed into quadcons that will be loaded onto transporters i ∈ Q. Defineinteger variables zi, j to represent the total number of quadcons loaded with commodity type j ∈Callocated to transporters i ∈ Q.


Table C.1: Sets Used in ILP FormulationC = {r, p,a,m} the set of commodity types:

r− rationsp− packaged POLa− ammunitionm− mixed stores

ALL = {1, ...,15} the set of all commoditiesRAT IONS = {1, ...,4} the set of rations:

1− Cbt rations2− water3−MRE4− fresh rations

POL = {5} the set of packaged POL:5− packaged POL

AMMO = {6} the set of ammunition:6− ammunition

MIXED = {7, ...,15} the set of mixed stores:7− engineering (construction)8− def (barrier)9− G & T10− amenities11− repair parts12− medical and dental13− postal14− other15− other

Table C.2: Payload Capacity Minus Container Weight

p̂1 = 10000,p̂2 = 4500,p̂3 = 5000,p̂4 = 16000,p̂5 = 8000,p̂6 = 8000,p̂7 = 16000,p̂8 = 8000,p̂9 = 8000,

p1 = p̂1,p2 = p̂2,p3 = p̂3,p4 = 13300,p5 = 5300,p6 = 5300,p7 = 12800,p8 = 4800,p9 = 4800.

Finally, define integer variables vehi to be the number of transporters i ∈ T that are required. Thenumber of cargo and 20′ container-carrying transporters is calculated by the equation

vehi = ∑j∈C

zi, j for i ∈ T \Q, (C.1)


and the number of transporters carrying quadcons is greater that the number of TEU:

vehi ≥∑j∈C

zi, j

4for i ∈ Q. (C.2)

C.4 Objective Function

The goal is to determine the minimum number of vehicles required to lift all required supplies,

min ∑i∈T\T RL

vehi. (C.3)

However, in the case of a tie, preference should be given to loading vehicles so as to minimize thenumber of trailers and also to minimize wasted vehicle payload capacity:

min ∑i∈T RL

vehi (C.4)

and

min ∑i∈T\T RL

vehi · p̂i− ∑i∈T\T RL

∑j∈ALL

w j · xi, j. (C.5)

This ILP objective function is modeled by choosing suitable weights to prioritize the objectives:

min ∑i∈T\T RL

100000∗ vehi + ∑i∈T RL

100∗ vehi + ∑i∈T\T RL

vehi · p̂i− ∑i∈T\T RL

∑j∈ALL

w j · xi, j. (C.6)

C.5 Constraints

All supplies must be lifted by the set of transporters. This is modeled as

∑i∈T

xi, j = l j for all j ∈ ALL. (C.7)

The bulk restrictions of all transporters i ∈ T \Q must be respected,

∑j∈RAT IONS

xi, j ≤ bi · zi,r, (C.8)

∑j∈POL

xi, j ≤ bi · zi,p, (C.9)

∑j∈AMMO

xi, j ≤ bi · zi,a, (C.10)

∑j∈MIXED

xi, j ≤ bi · zi,m, (C.11)


as well as payload restrictions of transporters: for i ∈ T \Q,

∑j∈RAT IONS

w j · xi, j ≤ pi · zi,r, (C.12)

∑j∈POL

w j · xi, j ≤ pi · zi,p, (C.13)

∑j∈AMMO

w j · xi, j ≤ 0.8 · pi · zi,a, (C.14)

∑j∈MIXED

w j · xi, j ≤ pi · zi,m. (C.15)

Note that constraint (C.14) restricts vehicles loaded with ammunition to 80% of the vehicles payloadcapacity. When loading quadcons (to be placed on transporters i ∈ Q), the bulk capacity of fourpallets per quadcon must be respected:

∑j∈RAT IONS

xi, j ≤ 4 · zi,r, (C.16)

∑j∈POL

xi, j ≤ 4 · zi,p, (C.17)

∑j∈AMMO

xi, j ≤ 4 · zi,a, (C.18)

∑j∈MIXED

xi, j ≤ 4 · zi,m. (C.19)

The payload capacity of a quadcon is 4280 lbs, requiring the constraints:

∑j∈RAT IONS

w j · xi, j ≤ 4280 · zi,r, (C.20)

∑j∈POL

w j · xi, j ≤ 4280 · zi,p, (C.21)

∑j∈AMMO

w j · xi, j ≤ 0.8 ·4280 · zi,a, (C.22)

∑j∈MIXED

w j · xi, j ≤ 4280 · zi,m. (C.23)

To model ammunition restrictions, quadcons carrying ammunition were loaded to 80% (constraint(C.22)). To ensure that groups of four quadcons could be placed together on transporters withoutexceeding the transporter payload capacities, the expected weight of a quadcon carrying four pallets


of a commodity was calculated,

∑j∈RAT IONS

w j · l j

∑j∈RAT IONS

l j·4 = EXPQr, (C.24)

∑j∈POL

w j · l j

∑j∈POL

l j·4 = EXPQp, (C.25)

∑j∈AMMO

w j · l j

∑j∈AMMO

l j·4 = EXPQa, (C.26)

∑j∈MIXED

w j · l j

∑j∈MIXED

l j·4 = EXPQm. (C.27)

The expected weights were used to form constraints so that the average weight of a representativeTEU would satisfy the transporter’s payload limitation:

EXPQr · zi,r +EXPQp · zi,p +EXPQa · zi,a +EXPQm · zi,m ≤ vehi · pi. for i ∈ Q (C.28)

If the average weight of the quadcons is too heavy, leading to over-weight TEUs, then constraint(C.28) will drive the number of vehicles up, simulating either placing empty quadcons beside fullones or spreading out the pallets among more quadcons, until an acceptable average weight of aTEU is achieved.

The number of trailers cannot exceed the number of vehicles that can pull them,

veh2 ≤ veh3, (C.29)

veh5 + veh8 ≤ veh6 + veh9, (C.30)

and ammunition cannot be carried on trailers:

zi,a = 0 for all i ∈ T RL. (C.31)




Annex D: Centralized Optimization Results

We present the detailed ILP results for the six vehicle configurations. The figures found in this sec-tion are snapshots from a spreadsheet that was used for result verification. Each table correspondsto a specific vehicle mix. This is indicated on the table heading. The tables are colour-coded foreasier interpretation of the ILP solution:– The first three columns specify the commodity name, weight per pallet, and number of pallets to

be lifted.– The remaining 9 columns (with first 3 rows in blue) represent the different transporter possibili-

ties.– The dark green row specifies how many transporters of each type are used.– The following four rows, coloured orange, gray, yellow, and green, show how many transporters

of each type are used per commodity group - rations, POL, ammunition, and mixed stores re-spectively. For quadcon transporters (last 3 main columns), these rows indicate the number ofquadcons used.

– The next set of coloured rows indicate where individual pallets of a particular store are to beloaded.

– The last four 4-row coloured blocks show how much weight and bulk is loaded, per commoditytype, compared to the capacity for each transporter.

The results are presented in the following order:






6. MSVS LHS and MSVS Cargo vehicles with respective trailers, HLVW PLS, HLVW Cargo,using 20′ containers or quadcons.


Num

ber

Con

tain

er

Trls

Tow

C

onta

iner

Trai

lers

HLV

W (C

argo

)M

SV

S (4

.5T)

C

argo

MS

VS

Car

go T

rl20

Ft o

n P

LS20

Ft o

n M

SV

S

LHS

20 F

t on

LHS

Trl

10 T

on

PLS

MS

VS

LH

SM

SV

S

LHS

Trl

0.0

27.0

1010

1020

2020

44

410

000

4500

5,00

013

,300

5,30

05,

300

12,8

004,

800

4,80

01.

010.

981.

020.

991.

020.

990

00

01

00

00

SH

OU

LD W

E U

SE

TR

AN

SP

OR

TER

?

Cla

ss

Nam

eW

eigh

t/ pa

llet

Tota

l Pal

lets

to

be

lifte

d0.

00.

00.

0O

BJE

CTI

VE:

0.0

0.0

0.0

0.0

27.0

0.0

0.0

0.0

0.0

Qua

dcnu

mbe

r of

26.7

3<-

Min

imiz

e nu

mbe

r of v

ehic

les

times

pre

fere

nce

fact

or0.

00.

00.

00.

06.

00.

00.

00.

00.

027

.00.

00.

00.

00.

01.

00.

00.

00.

00.

024

206.

00.

00.

00.

00.

015

.00.

00.

00.

00.

027

2420

6.0

<-M

inim

ize

Num

of V

eh A

ND

unu

sed

wei

ght c

apac

ity0.

00.

00.

00.

05.

00.

00.

00.

00.

0I

Cbt

Rat

ion s

698

110.

00.

00.

00.

011

.00.

00.

00.

00.

011

.0I

Wat

er90

022

0.0

0.0

0.0

0.0

22.0

0.0

0.0

0.0

0.0

22.0

00

0I

MR

E10

060

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

IFr

esh

Rat

ions

350

00.

00.

00.

00.

00.

00.

00.

00.

00.

00.

0III

PO

L P

acka

ged

425

100.

00.

00.

00.

010

.00.

00.

00.

00.

010

.0V

Am

mo

755

840.

00.

00.

00.

084

.00.

00.

00.

00.

084

.042

95

IV E

ngr S

tore

s (C

onst

ruct

ion)

544

170.

00.

00.

00.

017

.00.

00.

00.

00.

017

.0

IVD

ef S

tore

s (B

arrie

r)28

821

0.0

0.0

0.0

0.0

21.0

0.0

0.0

0.0

0.0

21.0

IIG

&T

300

140.

00.

00.

00.

014

.00.

00.

00.

00.

014

.0W

iegh

t Lift

ed11

8894

VI

Am

eniti

es15

015

0.0

0.0

0.0

0.0

15.0

0.0

0.0

0.0

0.0

15.0

Wei

gth

Cap

acity

1431

00.0

IXR

epai

r Par

ts50

01

0.0

0.0

0.0

0.0

1.0

0.0

0.0

0.0

0.0

1.0

Diff

eren

ce24

206.

0

VIII

Med

and

Den

tal

Sto

res

100

110.

00.

00.

00.

011

.00.

00.

00.

00.

011

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oal i

s to

min

imiz

e nu

mbe

r of v

ehic

les

and

unus

ed w

eigh

t cap

acity

IXP

osta

l10

04

0.0

0.0

0.0

0.0

4.0

0.0

0.0

0.0

0.0

4.0

spar

e 0

00.

00.

00.

00.

00.

00.

00.

00.

00.

00.

0sp

are

00

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

210

210.

011

8894

Vol

ume

Con

train

t0.

00.

00.

00.

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.00.

00.

00.

00.

0D

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0.0

0.0

0.0

0.0

120.

00.

00.

00.

00.

0W

eigh

t C

onst

rain

t0.

00.

00.

00.

027

478.

00.

00.

00.

00.

00.

00.

00.

00.

031

800.

00.

00.

00.

00.

0

PER

CEN

TAG

E U

SEC

ontra

int

0.0

0.0

0.0

0.0

10.0

0.0

0.0

0.0

0.0

HLV

W C

argo

MS

VS

CAM

SV

S T

RL

0.0

0.0

0.0

0.0

20.0

0.0

0.0

0.0

0.0

Rat

ions

Wei

ght

0.0

0.0

0.0

0.0

4250

.00.

00.

00.

00.

0P

OL

0.0

0.0

0.0

0.0

5300

.00.

00.

00.

00.

0A

mm

oM

ixed

Vol

ume

Con

train

t0.

00.

00.

00.

084

.00.

00.

00.

00.

00.

00.

00.

00.

030

0.0

0.0

0.0

0.0

0.0

<--N

o A

mm

o on

Tra

ilers

Wei

ght

Con

stra

int

0.0

0.0

0.0

0.0

6342

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

6360

0.0

0.0

0.0

0.0

0.0

<--N

o A

mm

o on

Tra

ilers

<--A

mm

o C

arry

ing

Vehi

cles

Loa

ded

at 8

0%

Vol

ume

Con

train

t0.

00.

00.

00.

083

.00.

00.

00.

00.

00.

00.

00.

00.

010

0.0

0.0

0.0

0.0

0.0

Wei

ght

Con

stra

int

0.0

0.0

0.0

0.0

2374

6.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

2650

0.0

0.0

0.0

0.0

0.0

MSV

S LH

S

Vehs

/Trls

Car

ryin

g 20

Ft C

onta

iner

sVe

hs/T

rls C

arry

ing

Qua

dsC

argo

Veh

icle

s th

at d

on't

carr

y co

ntai

ners

Wei

ght p

er F

leet

Wei

ght p

er F

leet

Tota

l Li

fted

Ave

Wgt

x N

o Q

uad

Max

wei

ght/f

leet

Tota

l Pal

lets

per

Fle

etM

ax P

alle

ts p

er F

leet

Wei

ght p

er F

leet

Rat

ion

Con

stra

ints

PO

L C

onst

rain

ts

Max

num

ber p

alle

ts/fl

eet

Wei

ght p

er F

leet

Max

Wei

ght/F

leet

Tota

l Pal

lets

per

Fle

et

Tota

l Pal

lets

per

Fle

etM

ax n

umbe

r pal

lets

/flee

t

Max

num

ber o

f pal

lets

M

ax w

eigh

t/veh

Veh

Leng

th in

m

Tota

l R

eqr

Rat

ion

Req

rP

OL

Req

r

Mix

ed R

eqr

Am

mo

Req

<-M

inim

ize

num

ber o

f veh

icle

s<-

Min

imiz

e un

used

wei

ght c

apac

ity

Max

Num

ber p

alle

ts F

leet

Max

wei

ght/f

leet

Am

mo

Con

stra

ints

Mix

ed C

onst

rain

ts

Max

wei

ght/f

leet

Tota

l Pal

lets

per

Fle

et


Num

ber

Con

tain

er

Trls

Tow

C

onta

iner

Trai

lers

HLV

W (C

argo

)M

SV

S (4

.5T)

C

argo

MS

VS

Car

go T

rl20

Ft o

n P

LS20

Ft o

n M

SV

S

LHS

20 F

t on

LHS

Trl

10 T

on

PLS

MS

VS

LH

SM

SV

S

LHS

Trl

0.0

20.0

1010

1020

2020

44

410

000

4500

5,00

013

,300

5,30

05,

300

12,8

004,

800

4,80

01.

010.

981.

020.

991.

020.

990

10

01

00

00

SH

OU

LD W

E U

SE

TR

AN

SP

OR

TER

?

Cla

ss

Nam

eW

eigh

t/ pa

llet

Tota

l Pal

lets

to

be

lifte

d0.

00.

00.

0O

BJE

CTI

VE:

0.0

7.0

0.0

0.0

20.0

0.0

0.0

0.0

0.0

Qua

dcnu

mbe

r of

26.6

6<-

Min

imiz

e nu

mbe

r of v

ehic

les

times

pre

fere

nce

fact

or0.

05.

00.

00.

01.

00.

00.

00.

00.

027

.00.

01.

00.

00.

00.

00.

00.

00.

00.

018

606.

00.

00.

00.

00.

015

.00.

00.

00.

00.

027

1860

6.0

<-M

inim

ize

Num

of V

eh A

ND

unu

sed

wei

ght c

apac

ity0.

01.

00.

00.

04.

00.

00.

00.

00.

0I

Cbt

Rat

ion s

698

110.

010

.00.

00.

01.

00.

00.

00.

00.

011

.0I

Wat

er90

022

0.0

17.0

0.0

0.0

5.0

0.0

0.0

0.0

0.0

22.0

00

0I

MR

E10

060

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

IFr

esh

Rat

ions

350

00.

00.

00.

00.

00.

00.

00.

00.

00.

00.

0III

PO

L P

acka

ged

425

100.

010

.00.

00.

00.

00.

00.

00.

00.

010

.0V

Am

mo

755

840.

00.

00.

00.

084

.00.

00.

00.

00.

084

.042

95

IV E

ngr S

tore

s (C

onst

ruct

ion)

544

170.

06.

00.

00.

011

.00.

00.

00.

00.

017

.0

IVD

ef S

tore

s (B

arrie

r)28

821

0.0

0.0

0.0

0.0

21.0

0.0

0.0

0.0

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21.0

IIG

&T

300

140.

00.

00.

00.

014

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00.

00.

00.

014

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iegh

t Lift

ed11

8894

VI

Am

eniti

es15

015

0.0

0.0

0.0

0.0

15.0

0.0

0.0

0.0

0.0

15.0

Wei

gth

Cap

acity

1375

00.0

IXR

epai

r Par

ts50

01

0.0

1.0

0.0

0.0

0.0

0.0

0.0

0.0

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1.0

Diff

eren

ce18

606.

0

VIII

Med

and

Den

tal

Sto

res

100

110.

03.

00.

00.

08.

00.

00.

00.

00.

011

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oal i

s to

min

imiz

e nu

mbe

r of v

ehic

les

and

unus

ed w

eigh

t cap

acity

IXP

osta

l10

04

0.0

0.0

0.0

0.0

4.0

0.0

0.0

0.0

0.0

4.0

spar

e 0

00.

00.

00.

00.

00.

00.

00.

00.

00.

00.

0sp

are

00

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

210

210.

011

8894

Vol

ume

Con

train

t0.

027

.00.

00.

06.

00.

00.

00.

00.

0D

ON

’T D

ELE

TE!!

0.0

50.0

0.0

0.0

20.0

0.0

0.0

0.0

0.0

Wei

ght

Con

stra

int

0.0

2228

0.0

0.0

0.0

5198

.00.

00.

00.

00.

00.

022

500.

00.

00.

053

00.0

0.0

0.0

0.0

0.0

PER

CEN

TAG

E U

SEC

ontra

int

0.0

10.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

HLV

W C

argo

MS

VS

CAM

SV

S T

RL

0.0

10.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Rat

ions

54.0

Wei

ght

0.0

4250

.00.

00.

00.

00.

00.

00.

00.

0P

OL

100.

00.

045

00.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Am

mo

Mix

ed10

0.0

Vol

ume

Con

train

t0.

00.

00.

00.

084

.00.

00.

00.

00.

00.

00.

00.

00.

030

0.0

0.0

0.0

0.0

0.0

<--N

o A

mm

o on

Tra

ilers

Wei

ght

Con

stra

int

0.0

0.0

0.0

0.0

6342

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

6360

0.0

0.0

0.0

0.0

0.0

<--N

o A

mm

o on

Tra

ilers

<--A

mm

o C

arry

ing

Vehi

cles

Loa

ded

at 8

0%

Vol

ume

Con

train

t0.

010

.00.

00.

073

.00.

00.

00.

00.

00.

010

.00.

00.

080

.00.

00.

00.

00.

0W

eigh

t C

onst

rain

t0.

040

64.0

0.0

0.0

1968

2.0

0.0

0.0

0.0

0.0

0.0

4500

.00.

00.

021

200.

00.

00.

00.

00.

0

Con

stra

ints

<-M

inim

ize

num

ber o

f veh

icle

s<-

Min

imiz

e un

used

wei

ght c

apac

ity

Max

Num

ber p

alle

ts F

leet

Max

wei

ght/f

leet

Am

mo

Con

stra

ints

Mix

ed C

onst

rain

ts

Max

wei

ght/f

leet

Tota

l Pal

lets

per

Fle

etTota

l R

eqr

Rat

ion

Req

rP

OL

Req

r

Mix

ed R

eqr

Am

mo

Req

Max

num

ber o

f pal

lets

M

ax w

eigh

t/veh

Veh

Leng

th in

m

PO

L C

onst

rain

ts

Max

num

ber p

alle

ts/fl

eet

Wei

ght p

er F

leet

Max

Wei

ght/F

leet

Tota

l Pal

lets

per

Fle

et

Tota

l Pal

lets

per

Fle

etM

ax n

umbe

r pal

lets

/flee

t

Wei

ght p

er F

leet

Wei

ght p

er F

leet

Tota

l Li

fted

Ave

Wgt

x N

o Q

uad

Max

wei

ght/f

leet

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r pal

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num

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ax w

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th in

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l R

eqr

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r

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mo

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ize

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ber

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tain

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argo

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go T

rl20

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n P

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OU

LD W

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AN

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ss

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llet

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l Pal

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mo

on T

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mo

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ryin

g Ve

hicl

es L

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d at

80%

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ume

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train

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010

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010

600.

00.

042

80.0

0.0

Con

stra

ints

Tota

l Pal

lets

to b

e lif

ted

= To

tal L

ifted

4.5

T Tr

aile

rs =

< M

SV

S C

argo

sLH

S T

raile

rs =

< M

SV

S L

HS

No

vehs

for Q

uad

=< N

o Q

uad*

4N

o ve

hs fo

r 20

ft =2

0 ft

Ave

rage

in

clud

e C

ont

Rat

ions

833

3331

4131

PO

L 42

517

0025

00A

mm

o75

530

2038

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d S

tore

s28

611

4419

44

16 A

ll ve

hs w

ith Q

uads

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/Trls

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ryin

g 20

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iner

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hs/T

rls C

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ing

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dsC

argo

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icle

s th

at d

on't

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y co

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ners

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ght p

er F

leet

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ght p

er F

leet

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l Li

fted

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x N

o Q

uad

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wei

ght/f

leet

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l Pal

lets

per

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etM

ax P

alle

ts p

er F

leet

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ght p

er F

leet

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ion

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stra

ints

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L C

onst

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t s

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num

ber p

alle

ts/fl

eet

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ght p

er F

leet

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ght/F

leet

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l Pal

lets

per

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et

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l Pal

lets

per

Fle

etM

ax n

umbe

r pal

lets

/fle e

Max

num

ber o

f pal

lets

M

ax w

eigh

t/veh

Veh

Leng

th in

m

Tota

l R

eqr

Rat

ion

Req

rP

OL

Req

r

Mix

ed R

eqr

Am

mo

Req

<-M

inim

ize

num

ber o

f veh

icle

s<-

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imiz

e un

used

wei

ght c

apac

ity

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Num

ber p

alle

ts F

leet

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ghte

d av

erag

e of

nu

mbe

r of p

alle

ts a

nd

wei

ght p

er c

omm

odity

Pal

let W

eigh

t for

Com

mod

ity

Gro

ups

X 4

pal

lets

per

Qua

d

Max

wei

ght/f

leet

Am

mo

Con

stra

ints

Mix

ed C

onst

rain

ts

Max

wei

ght/f

leet

Tota

l Pal

lets

per

Fle

et




Annex E: Decentralized Optimization Results

We present the decentralized ILP results for the optimal configuration determined in Section 6. Thelift requirement and allocation for the five camps is presented.

Cam

p 1

Num

ber

Con

tain

er

Trls

Vehs

to

Tow

C

onta

iner

Trai

lers

HLV

W C

argo

MSV

W C

argo

MSV

S C

argo

Tr

aile

rH

LVW

PL

SM

SVS

LHS

MSV

S LH

S Tr

aile

rH

LVW

w

Qua

d

MSV

S LH

S w

Q

uad

MSV

S LS

H T

rl w

Q

uad

1010

1020

2020

44

410

000

4500

5,00

013

,300

5,30

05,

300

12,8

004,

800

4,80

01.

010.

981.

020.

991.

020.

991

11

11

11

11

SH

OU

LD W

E U

SE

TR

AN

SP

OR

TER

?

Cla

ss

Nam

eW

eigh

t/ pa

llet

Tota

l Pal

lets

to

be

lifte

d0.

02.

0O

BJE

CTI

VE:

0.0

1.0

1.0

0.0

2.0

0.0

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0.0

6.0

Qua

dcnu

mbe

r of

2.96

<- M

inim

ize

num

ber o

f veh

icle

s tim

es p

refe

renc

e fa

ctor

1.0

1.0

1.0

3.0

1.0

1270

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031

570.

2<-

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imiz

e N

um o

f Veh

AN

D u

nuse

d w

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t cap

acity

1.0

4.0

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bt R

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ns69

85

5.0

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ater

900

95.

04.

09.

00

095

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esh

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ions

350

00.

0III

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L P

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ged

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mo

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onst

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ion)

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0

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s (B

arrie

r)28

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5.0

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&T

300

66.

06.

0W

iegh

t Lift

ed13

829.

8137

5V

IA

men

ities

150

66.

06.

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eigt

h C

apac

ity15

100.

0IX

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air P

arts

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01.

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iffer

ence

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and

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tal

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res

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oal i

s to

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imiz

e nu

mbe

r of v

ehic

les

and

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ed w

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t cap

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l10

02

2.0

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e 0

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are

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9.81

375

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ume

Con

train

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05.

00.

00.

00.

00.

00.

04.

0D

ON

’T D

ELE

TE!!

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10.0

10.0

0.0

0.0

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0.0

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ght

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stra

int

0.0

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90.0

0.0

0.0

0.0

0.0

0.0

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.00.

045

00.0

5000

.00.

00.

00.

00.

00.

042

80.0

PER

CEN

TAG

E U

SEC

ontra

int

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

4.0

HLV

W C

argo

MS

VS

CAM

SV

S T

RL

0.0

0.0

0.0

0.0

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Annex F: Simulation Statistics

0.00

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Trailers



Fleet Mix

Hours Centralized

Decentralized

Figure F.1: RP Loading Times (hrs)

Table F.1: RP Load Times (hrs)










→ quadcons? Yes







Table F.2: Convoy Duration for Different Fleets (hrs)










→ quadcons? Yes






2.20

2.25

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2.35

2.40

2.45

2.50

2.55

2.60

MSVS LHS MSVS LHSand Cargo

MSVS LHSand Cargo

withQuadcons

MSVS LHSand Cargo

with Trailers

MSVS LHSand Cargo

with Trailersand Quadcons


Fleet Mix

Hours

Centralized

Decentralized

Figure F.2: Convoy Duration for Various Fleet Mixes (hrs)


Table F.3: Unload and Load at Camp Time (hrs)

Centralized DecentralizedUnload/ReloadPallets

UnloadReloadContainer

Diff. Unload/ReloadPallets

Unload/LoadContainer

Diff.

MSVS LHSAverage 0.00 3.44 3.44 0.00 4.99 4.99Min 0.00 3.11 3.11 0.00 4.19 4.19Max 0.00 3.90 3.90 0.00 5.94 5.94Average 2.07 2.57 0.50 3.45 3.71 0.26

MSVS Cargo and Min 1.78 2.16 0.39 2.95 3.01 0.05MSVS LHS Max 2.39 3.01 0.62 3.94 4.45 0.52MSVS Cargo, Average 0.00 6.45 6.45 5.56 7.35 1.79MSVS LHS with Min 0.00 5.48 5.48 4.61 6.09 1.48trailers Max 0.00 7.53 7.53 6.75 9.03 2.28MSVS Cargo, Average 1.98 2.48 0.50 2.24 4.59 2.35MSVS LHS with Min 1.66 2.17 0.51 1.91 3.77 1.85quadcons Max 2.30 2.85 0.55 2.72 5.51 2.80MSVS Cargo, Average 0.00 6.08 6.08 3.93 4.02 0.09MSVS LHS with Min 0.00 5.02 5.02 3.09 3.22 0.14trailers and quadcons Max 0.00 7.31 7.31 5.08 4.98 -0.09HLVS PLS & Cargo, Average 3.65 3.82 0.17 3.74 4.37 0.62MSVS LHS & Cargo, Min 2.68 3.02 0.34 2.82 3.43 0.62trailers and quadcons Max 4.81 4.68 -0.13 4.95 5.38 0.43

0.00

1.00

2.00

3.00

4.00

5.00

6.00

7.00

8.00




Trailers



Fleet Mix


Figure F.3: Avgerage Unload and Load at Camp Time (hrs) Dominated by Time to Load Containers


Table F.4: Unload at RP Time (hrs)

Centralized DecentralizedUnload/ReloadPallets

UnloadReloadContainer

Diff. Unload/ReloadPallets

Unload/LoadContainer

Diff.

MSVS LHSAverage 0.00 1.05 1.05 0.00 1.31 1.31Min 0.00 0.86 0.86 0.00 1.10 1.10Max 0.00 1.32 1.32 0.00 1.55 1.55Average 0.56 0.81 0.25 1.01 0.82 -0.19

MSVS Cargo and Min 0.38 0.63 0.25 0.79 0.61 -0.18MSVS LHS Max 0.75 1.03 0.28 1.29 1.04 -0.26MSVS Cargo, Average 0.00 2.10 2.10 2.00 2.68 0.68MSVS LHS with Min 0.00 1.70 1.70 1.31 2.24 0.93trailers Max 0.00 2.58 2.58 2.89 3.16 0.26MSVS Cargo, Average 0.56 0.78 0.23 0.61 0.96 0.35MSVS LHS with Min 0.36 0.58 0.23 0.41 0.73 0.32quadcons Max 0.74 0.98 0.24 0.75 1.17 0.42MSVS Cargo, Average 0.00 1.98 1.98 1.33 1.48 0.15MSVS LHS with Min 0.00 1.56 1.56 0.82 1.18 0.35trailers and quadcons Max 0.00 2.50 2.50 1.72 1.86 0.14HLVS PLS & Cargo, Average 1.13 1.22 0.09 1.38 1.38 0.00MSVS LHS & Cargo, Min 0.72 0.80 0.08 0.90 1.08 0.18trailers and quadcons Max 1.74 1.49 -0.25 1.74 1.74 0.00

0.00

0.50

1.00

1.50

2.00

2.50

3.00


MSVS Cargo andLHS with Quadcons

MSVS Cargo andLHS with Trailers

MSVS Cargo andLHS with Trailers

and Quadcons


Fleet Mix

Hou

rs


Figure F.4: Unload at RP (hrs) for Vehicles Carrying Containers


List of symbols/abbreviations/acronyms/initialisms

Cbt CombatCF Canadian ForcesCoy CompanyDLR Directorate Land RequirementsDMGOR Directorate Material Group Operational ResearchDP Delivery PointDROGM Directeur - Recherche Opérationnelle (Groupe des matériels)G & T General and TechnicalHLVW Heavy Logistics Vehicle Wheeledhrs hoursILP Integer Linear ProgramIMP Individual Meal Packin InchesISO International Standards Organizationkg kilogramskm kilometerskph kilometers per hourLAV Light Armoured VehicleLHS Load Handling SystemMLVW Medium Logistics Vehicle WheeledMRE Meals Ready to EatMSVS Medium Support Vehicle SystemMDBF Mean Distance Between FailuresNATO North Atlantic Treaty OrganizationPLS Palletized Loading Systemplt PalletsPOL Petroleum Oils and LubricantsRP Replenishment PointSCP Système de Chargement PalettiséSDH Staff Data HandbookSMP Standard Military PatternSOR Statement of RequirementsSVSM Système de Véhicule de Soutien MoyenTEU Twenty Foot Equivalent Unittrls Trailersvehs VehiculesVLLR Véhicules Logistique Lourd à Roueswgt Weight




Distribution letter

3552-1 (DMGOR)

27 November 2006

Distribution List


Reference: Bohdan L. Kaluzny and Adrian J. Erkelens, The Optimal MSVS Fleet for First-LineReplenishment, DRDC CORA TR 2006–026, November 2006 (enclosed).

1. Please find enclosed the Defence Research and Development Canada—Centre forOperational Research and Analysis Technical Report DRDC CORA TR 2006–026, entitled TheOptimal MSVS Fleet for First-Line Replenishment. The report analyzes the use of MSVS vehicles,trailers, and containers for first-line replenishment and recommends an optimal mix of MSVSLoad Handling System (LHS) and Cargo variants.

2. The CF intends to purchase 1,500 MSVS vehicles. One of the tasks of the MSVS variants,a 4.5 ton cargo vehicle and an 8 ton LHS, will be to transport the stores and equipment necessary tosupport deployed forces. This study determined the daily stores required by a model organization,computed the minimal number of vehicles required to resupply the unit using various vehicle fleetconfigurations, analyzed the replenishment cycle for these configurations under centralized anddecentralized scenarios, and recommended an optimal mix of MSVS LHS and Cargo variants.

3. The optimization and simulation models developed in this study can be customized forfuture vehicle/fleet loading analysis. Questions or comments are welcomed and may be addressedto Bohdan L. Kaluzny at (613) 944-5203 or by e-mail at [email protected]. Electroniccopies of this report are available upon request ([email protected]) or directly from the ORDintranet site (http://ord.mil.ca/pages/corporate/library_e.asp).

R. G. DickinsonDirector Joint and Strategic Analysis

Distribution List (see page 2)

Enclosures: 1


Distribution List

Internal

DLRDLR 6PD MSVS (3)PM MSVSDLSS (2)LFDI (2)DAD 9 (2)DRDC CORA//DG CORA/DOR(Joint)/DOR(MLA)/Chief Scientist (1 copy on circulation)DRDC CORA/LFORTDRDC CORA Library (2)DRDKIM (2)Spares (5)


DOCUMENT CONTROL DATA(Security classification of title, body of abstract and indexing annotation must be entered when document is classified)

1. ORIGINATOR (The name and address of the organization preparing thedocument. Organizations for whom the document was prepared, e.g. Centresponsoring a contractor’s report, or tasking agency, are entered in section 8.)

Defence R&D Canada – CORADept. of National Defence, MGen G.R. Pearkes Bldg.,101 Colonel By Drive, Ottawa, Ontario, Canada K1A0K2

2. SECURITY CLASSIFICATION (Overallsecurity classification of the documentincluding special warning terms if applicable.)

UNCLASSIFIED

3. TITLE (The complete document title as indicated on the title page. Its classification should be indicated by the appropriateabbreviation (S, C or U) in parentheses after the title.)


4. AUTHORS (Last name, followed by initials – ranks, titles, etc. not to be used.)

Kaluzny, B.L.; Erkelens, A.J.

5. DATE OF PUBLICATION (Month and year of publication ofdocument.)

December 2006

6a. NO. OF PAGES (Totalcontaining information.Include Annexes,Appendices, etc.)

88

6b. NO. OF REFS (Totalcited in document.)

23

7. DESCRIPTIVE NOTES (The category of the document, e.g. technical report, technical note or memorandum. If appropriate, enterthe type of report, e.g. interim, progress, summary, annual or final. Give the inclusive dates when a specific reporting period iscovered.)

Technical Report

8. SPONSORING ACTIVITY (The name of the department project office or laboratory sponsoring the research and development –include address.)

Defence R&D Canada – CORADept. of National Defence, MGen G.R. Pearkes Bldg., 101 Colonel By Drive, Ottawa, Ontario,Canada K1A 0K2

9a. PROJECT NO. (The applicable research and developmentproject number under which the document was written.Please specify whether project or grant.)

N/A

9b. GRANT OR CONTRACT NO. (If appropriate, the applicablenumber under which the document was written.)

10a. ORIGINATOR’S DOCUMENT NUMBER (The officialdocument number by which the document is identified by theoriginating activity. This number must be unique to thisdocument.)

DRDC CORA TR 2006–026

10b. OTHER DOCUMENT NO(s). (Any other numbers which maybe assigned this document either by the originator or by thesponsor.)

11. DOCUMENT AVAILABILITY (Any limitations on further dissemination of the document, other than those imposed by securityclassification.)( X ) Unlimited distribution( ) Defence departments and defence contractors; further distribution only as approved( ) Defence departments and Canadian defence contractors; further distribution only as approved( ) Government departments and agencies; further distribution only as approved( ) Defence departments; further distribution only as approved( ) Other (please specify):

12. DOCUMENT ANNOUNCEMENT (Any limitation to the bibliographic announcement of this document. This will normally correspondto the Document Availability (11). However, where further distribution (beyond the audience specified in (11)) is possible, a widerannouncement audience may be selected.)

13. ABSTRACT (A brief and factual summary of the document. It may also appear elsewhere in the body of the document itself. It is highlydesirable that the abstract of classified documents be unclassified. Each paragraph of the abstract shall begin with an indication of thesecurity classification of the information in the paragraph (unless the document itself is unclassified) represented as (S), (C), (R), or (U).It is not necessary to include here abstracts in both official languages unless the text is bilingual.)

The Medium Support Vehicle System (MSVS) Project will purchase 1,500 standard military pat-tern (SMP) vehicles to support deployable units. One of the tasks of the SMP MSVS variants, a4.5 ton cargo vehicle and an 8 ton Load Handling System (LHS), will be to transport the storesand equipment necessary to support deployed forces. This study determined the daily storesrequired by a model organization, computed the minimal number of vehicles required to resupplythe unit using various fleet configurations, analyzed the replenishment cycle for these configura-tions under centralized and decentralized scenarios, and recommended an optimal mix of MSVSLHS and Cargo variants.

14. KEYWORDS, DESCRIPTORS or IDENTIFIERS (Technically meaningful terms or short phrases that characterize a document and couldbe helpful in cataloguing the document. They should be selected so that no security classification is required. Identifiers, such asequipment model designation, trade name, military project code name, geographic location may also be included. If possible keywordsshould be selected from a published thesaurus. e.g. Thesaurus of Engineering and Scientific Terms (TEST) and that thesaurus identified.If it is not possible to select indexing terms which are Unclassified, the classification of each should be indicated as with the title.)

MSVSInteger Linear ProgramOptimizationFleet SizeSimulationReplenishmentForward ResupplyLift Requirement

DRDC CORA

www.drdc-rddc.gc.ca

Documents

Report - The Optimal MSVS Fleet for First-Line Replenishment