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CIRRELT
Intermodal Transportation
Teodor Gabriel Crainic
ESG UQAM&
CIRRELT - CRT
2© Teodor Gabriel Crainic 2006
Plan
What are we talking about?Container-based intermodal transportationSystem design (location)Fleet Management (empties)Perspectives
3© Teodor Gabriel Crainic 2006
What are we talking about?
4© Teodor Gabriel Crainic 2006
Intermodal Transportation
Simple and straightforward definition:Movement of a person or a load by a sequence of at least two transportation modes, the transfer from one mode to the next being performed at a (intermodal) terminalE.g., Door-to-door transportation of containers
Over long distancesOrigin → “land” transport → port → container ship → port → “land” transport → destination
5© Teodor Gabriel Crainic 2006
A “Strict” Definition
Movement of goodsOne and the same loading unit or vehicleA chain ofSeveral transportation modes (services)
CoordinationInteractions
Intermodal terminalsNo handling of the goods themselves
Door-to-door service European Conference of Ministers of Transport (1993)
6© Teodor Gabriel Crainic 2006
A More General Definition
Movement of goodsA chain (network)Several transportation modes (services)
Coordination (more or less) Interactions
Intermodal terminals“Door-to-door” service
7© Teodor Gabriel Crainic 2006
Many Things to Many People
Major instrument for E.U. policy aimed at switching freight from trucks & highways to more environment-friendly modes (rail, water)Dedicated rail services (subdivisions) to move large volumes of containers/trailers over long distances: the trans-continental “land bridges”Container transportationConsolidation carriers: local & long-haul operations, several long-haul types of services, with/without use of external services
8© Teodor Gabriel Crainic 2006
Many Things to Many People (2)
Uncontainerized cargoCourier (express) services National planningCity LogisticsTerminal (ports, airports, …) planning and operations
9© Teodor Gabriel Crainic 2006
Scope of Presentation
Container-based intermodal transportationIllustrative planning/operations management issuesOperations research models and methods
A very young fieldNo definite answersAn open invitation to join in !! ☺
10© Teodor Gabriel Crainic 2006
Plan
What are we talking about?Container-based intermodal transportationSystem design (location)Fleet Management (empties)Perspectives
11© Teodor Gabriel Crainic 2006
Intermodal Transportation – Containers
AdvantagesReduced cargo handlingIncreased security regarding damage and lossIncreased standardization of transportation and transfer equipmentIncreased automation of terminal operations
⇒Cost reduction, more efficient door-to-door transportation
Sustained growth
12© Teodor Gabriel Crainic 2006
Evolution of Container Traffic (Koh and Kim 2001)
5.8254.6200310.6280.02004
Growth rate (%)Container traffic (M)Year
8.6 304.02005
3.9240.620022.8 231.62001
10.9 225.3200010.0 203.219994.2153.519979.8137.21995
12.5 113.21993
13© Teodor Gabriel Crainic 2006
Intermodal Transportation – Containers (2)
Lifeline of world-wide trade and economyIncreasingly larger container ships for inter-continental transportation (liners)
These cannot berth at all portsIt is not economical to stop at many ports
Container mega portsNew coastal navigation feeder services (“regular” ships): mega ports and huge liners ↔ regular ports⇒A new link in the multi-modal chain
“New” long-distance rail services (double-stack)
14© Teodor Gabriel Crainic 2006
Intermodal Transportation – Containers (3)
Asia (Hong Kong, Singapore, …) to America or Europe:Origin → truck → port → large container ship (liner) → mega port → “small” container vessel → port →truck/rail/river → destinationContainer port terminal transformations for increased efficiency in loading/unloading operations and exchanges with land carriers
New terminals / Enhancement of existing onesAutomationIntelligent Transportation Systems
15© Teodor Gabriel Crainic 2006
Notes
Container intermodal transportation (& express courier / post services)
Customer: Customized serviceOperator(s): Hub-and-spoke network with consolidation
All long-haul transportation must address the issue of empty vehicle repositioning
Trade is unbalanced⇒Vehicle flows as well !!
Tight fleet size? Long distances?
16© Teodor Gabriel Crainic 2006
Plan
What are we talking about?Container-based intermodal transportationSystem design (location)Fleet Management (empties)Perspectives
17© Teodor Gabriel Crainic 2006
System and Service Design
Strategic decisions – System DesignLocate (intermodal) terminalsDirect/indirect customer (zone) servicePort/terminal dimensioning
Number of berthsSize of storage spaceType & number of various equipment types
Facility & service abandon, …
18© Teodor Gabriel Crainic 2006
System and Service Design (2)
Tactical decisions – Service DesignRoutes served (routes, stops, mode, equipment, …)Service frequency & scheduleCargo routingTerminal workloads
Container port terminal equipment assignmentTo sea-side and land-side operations
Not many contributions for container transportation
19© Teodor Gabriel Crainic 2006
System Design
Not many contributionsTactical or operational models to evaluate strategic strategiesPorts: queuing, simulation
Discrete location modelsConsolidation / hub terminals
Network design + locationSelect direct services/links
Aim to capture economies of scale associated to consolidation of freight
20© Teodor Gabriel Crainic 2006
System Design (2)
Location of facilities (terminals)Production-distributionHub locationLocation with balancing requirements
21© Teodor Gabriel Crainic 2006
Location with Balancing Requirements
Land part of an intermodal container transportation system (may be generalized)Use in-land container depots for more efficient operations and reduced empty travel
22© Teodor Gabriel Crainic 2006
“Traditional” Operations
Importingcustomer
Exportingcustomer
LoadedEmpty
23© Teodor Gabriel Crainic 2006
Operations with In-Land Depots
Importingcustomer
Exportingcustomer
LoadedEmpty
Empty balancing
24© Teodor Gabriel Crainic 2006
Location with Balancing Requirements (2)
Loaded movements are “profitable”Empty movements are not
Customer to depot: Return movementSupply of empties
Depot to customer: Demand satisfactionDemand for empties
Depot to depot: Repositioning of empty containers due to unbalances in supply/demand
25© Teodor Gabriel Crainic 2006
Location with Balancing Requirements Network
customers
customers
depots
demand
supply
k
D i'
Dip
Oip
Oi
sjkp
cijp
i
j
i'
26© Teodor Gabriel Crainic 2006(flows of empty containers)
customers
customers
depots
demand
supply
k
D i'
ijpxjkpw
Oi
i
j
i'
jy
'ki px
27© Teodor Gabriel Crainic 2006
Location with Balancing Formulation
Minimise
Subject to
[Demand / Flow conservation]
Z f y
c x c x s w
x O i C p P
x D i C p P
jj D
j
ijp ijp jip jip jkp jkpk Dj Dj Di Cp P
ijp ipj D
jip ipj D
=
+ + +
= ∈ ∈
= ∈ ∈
∈
∈∈∈∈∈
∈
∈
∑
∑∑∑∑∑
∑
∑
{ ( ) }
,
,
28© Teodor Gabriel Crainic 2006
Location with Balancing Formulation (2)
,
,
[Linking / Feasibility]
[Balancing] ,
0 ,
x O y i C j D p P
x D y i C j D p P
x w x w j D p P
x x i C j D p P
w j D k D p P
y
ijp ip j
jip ip j
ijpi C
kjpk D
jipi C
jkpk D
ijp jip
jkp
j
≤ ∈ ∈ ∈
≤ ∈ ∈ ∈
+ − − = ∈ ∈
≥ ∈ ∈ ∈
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∈ ∈ ∈ ∈∑ ∑ ∑ ∑
,
,
,
, ,
,
0
0
∈ ∈{ , }0 1 j D
29© Teodor Gabriel Crainic 2006
Plan
What are we talking about?Brief overview of freight transportationContainer-based intermodal transportationSystem design (location)Fleet Management (empties)Perspectives
30© Teodor Gabriel Crainic 2006
Operational Planning
Resource managementCrewsVehiclesPower (engines, etc.), and so on
Allocation – dispatching, schedulesMake sure the required resources are where they need to be when they need to be thereBe efficient !(Satisfy demand, achieve economic and service objectives, implement plan, obey laws, policies, …)
31© Teodor Gabriel Crainic 2006
Issues
Trade is unbalancedMoving goods results in unbalanced distribution of resources: crews, vehicles, etc.One needs to reposition resources for use in the following periods
Regular operations (if possible)Balancing operations (vehicles, power units, …)Crews travelling as passengers
The demand in following periods is a forecast
32© Teodor Gabriel Crainic 2006
Other Operational Issues
Real-time dispatchPacingReal-time routing adjustment…
33© Teodor Gabriel Crainic 2006
Consolidation Transportation
Transportation plan “guides” operationsIt includes guidelines for repositioning (it should …)“Indicative” schedules: Ad-hoc (real-time) procedures“Regular” demand planning: Short-term and real-time adjustment of plansScheduled operations: Repositioning must follow and “feed” schedules + real-time adjustmentWell-defined crew (personnel) schedules
34© Teodor Gabriel Crainic 2006
Customized Transportation
No plan !!Dynamic management and control of resources: routes, schedules, fleets, personnel, etc.Uncertainty plays important role
DemandTravel timesService times at customers and terminalsWeather, …
35© Teodor Gabriel Crainic 2006
The Empty Vehicle Repositioning Problem
Surpluses and deficits of empty vehiclesObserved at terminals “at the end” of the dayComputed with respect to the next period demand
Need to reposition for the next periodHow many vehicles (of what type) to move from a surplus location (origin) to a deficit location (destination)?
Much more decision freedom than in loaded transportationA cost activity with “no” profit
36© Teodor Gabriel Crainic 2006
History
Transportation model – static and deterministicKnown surpluses and deficits – No uncertaintiesNo (not important) travel time impact – StaticArrival times known (certain prediction)
All travel, loaded and empty, occurs during the same period
Single or fully substituable resources (vehicles)For certain LTL types, tactical planning, …
37© Teodor Gabriel Crainic 2006
History (2)
Deterministic, multi-period transshipment modelDifferent movements require different travel timesVehicles become empty at different moments (customer release times) Demand varies in time …The dynamic characteristic of the system represented through (dynamic, time-dependent) space-timenetworks
38© Teodor Gabriel Crainic 2006
Space-Time Networks
Nodes: Facilities – terminals, customers, etc. – at given time periods
A physical point is repeated at each period & activity Arcs: Movements in space and time
Independent, e.g., a truck moving by itselfGrouped, e.g., containers on flat cars (rail) or in a shipHolding decisions (vehicles or cargo)
39© Teodor Gabriel Crainic 2006
Space-Time Network (Simple)T
erm
inal
s
Time
Current period Future periodsInventory (holding) arcRepositioning arc
40© Teodor Gabriel Crainic 2006
Space-Time Network
Loaded movementEnd of horizon
Ter
min
als
Time
Current period Future periodsInventory (holding) arcRepositioning arc
41© Teodor Gabriel Crainic 2006
Challenges and Limitations
One may includeCapacitiesSeveral types of resourcesInventory costs
Stock out (rent, borrow, …)End of horizon value
Substitutions (and costs)Complex cost structures
Linear programming formulations with a few “complications”
42© Teodor Gabriel Crainic 2006
Challenges and Limitations (2)
Planning horizon length? End-of-horizon? Rolling horizon
Everything is deterministicTimes (travel, terminal operations, customer, …)Future demand, etc.
UtilizationStrictly scheduled railways with bookings
43© Teodor Gabriel Crainic 2006
The Uncertainty Factor
Times may varyDemand estimation is rarely preciseUnexpected demands and events Current decisions impact the future state of the system and future decisionsNeed to explicitly consider / model
Uncertainty – the stochastic nature – of the system and its environmentThe impact of current decisions on future system state and decisions
44© Teodor Gabriel Crainic 2006
The Uncertainty Factor (2)
Stochastic formulations and solution methodsA complex field: General approaches and, often, custom-designed methods Active research fieldFormulations
General stochastic programming and solution methods :
Few efficient applications to transport problems
45© Teodor Gabriel Crainic 2006
The Uncertainty Factor (3)
FormulationsRecourse formulations and rolling horizon methods
Nice application to regular-type systems (e.g., consolidation)
Stochastic formulation and solution strategies based on adaptive dynamic (linear) programming and decision/time-based decomposition
Time-Space multicommodity networksRecent developments with interesting results
46© Teodor Gabriel Crainic 2006
The Uncertainty Factor (4)
Challenges of stochastic formulationsProblem formulation (!!)Resolution (!!)
PlusRepresentation of resources and attributesForecastsAvailability and reliability of dataValidation of models and strategiesImplementation and follow up
47© Teodor Gabriel Crainic 2006
Container (Empty) Fleet Management
Major repositioning decisions over large geographical regions (e.g., inter-continental movements)
Similar to consolidation transportationAllocation of empty containers to customers
Similar to customized transportation Two applications in this talk
Allocation and management of a heterogeneous fleet of containers over a land zoneSingle-commodity dynamic container allocation for liner operators (regular ocean navigation lines)
48© Teodor Gabriel Crainic 2006
Heterogeneous Fleet
Given region (continent)Loaded containers arrive (e.g., maritime network) to be delivered to customersEmpty containers arrive or leave to balance system-wide operations (demand)Customers empty containers that must be moved out Customers require empty containers for future loaded shipmentsOne must manage the fleet of containers for maximum profit, while satisfying demand
49© Teodor Gabriel Crainic 2006
Heterogeneous Fleet (2)
Several types of containers (e.g., 20 or 40 feet, normal box, thermal, refrigerated, etc.)Substitutions allowed: conditions and costs“Massive” inter-depot balancing movementsDue-dates at some terminals (e.g., ship schedules)Time windows at customersDemand (at least part of) fluctuates in time and is forecasted onlyUnloading time at customer: UncertainTravel times may be uncertain as well
50© Teodor Gabriel Crainic 2006
Heterogeneous Fleet (3)
Containers may be damaged partially (repairs) or totallyExternal sources (buy, rent) of empty containersCentralized empty container fleet managementLoaded movements not “managed” Associated problem: global management of the empty & loaded container movements together with vehicle routesA single model not computationally feasible ⇒hierarchical DSS
51© Teodor Gabriel Crainic 2006
Main Movements(No Time/Container Type Specifics)
Harbour
Depot j
Depot kSupplycustomer
Demandcustomer
Externalpool ofemptycontainers
52© Teodor Gabriel Crainic 2006
Formulations
Crainic, Dejax, Gendreau (93)Single and multicommodity deterministic formulationsA two-stage, restricted recourse single commodity, stochastic modelMulticommodity stochastic formulations may be defined
53© Teodor Gabriel Crainic 2006
Formulations (2)
Space-time diagram Generalized network (substitutions)Multiple-period transportation arcsHolding arcs (depots)Inter-depot balancing arcs
Stochastic elementsDemand (of known and possible customers)Release time from supply customers
⇒Inventory levels⇒Import and export (border points, external pool)
54© Teodor Gabriel Crainic 2006
Formulations (3)
Minimize total cost over the time horizonFlow conservation (over time and space, including access to external pool)
Supply at supply customersDemandContainer substitution
Depot (and port) inventories (each container type)Bounds on inter-depot balancing flows“End-of-horizon” restrictions (e.g., limits on “final”inventories)
55© Teodor Gabriel Crainic 2006
Single Commodity Liner
Cheung and Chen 1998A container liner company offers regular service among a number of portsCarries loaded and, space permitting, empty containersShip schedules known and fixed1 ship / period between 2 portsDemand less than ship capacity1 container type
56© Teodor Gabriel Crainic 2006
Formulation
Two-stage stochastic model Time-space network with random arc capacitiesMinimize the (expected) total costRolling-horizon mode
Sources of randomnessShip residual capacity for taking empty containers (given port and time period)Demand for containers at each port/timeSupply of containers at each port /time before unloading from ships
57© Teodor Gabriel Crainic 2006
Formulation (2)
Minimize total expected (cost – revenue from demand)Ship container conservation: containers unloadedShip container conservation: containers loaded for repositioningPort container conservation / demand satisfactionShip residual capacity for repositioningNumber of leased containers
58© Teodor Gabriel Crainic 2006
Plan
What are we talking about?Brief overview of freight transportationContainer-based intermodal transportationSystem design (location)Fleet Management (empties)Perspectives
59© Teodor Gabriel Crainic 2006
Perspectives
Intermodal transportation Growing steadily & should continue to growContainers and other modes
Profound modifications to the economic, regulatory, technological, social and political environment of industryGlobalization, automation, ITS, e-logistics, security, …Need for innovative and enhanced planning and management proceduresOpportunities for Operations Research and Transportation Science
60© Teodor Gabriel Crainic 2006
Perspectives (2)
A number of research efforts and important resultsMuch more work is needed!Many issues application areas not/little addressedIndustry evolution ⇒ New problemsPorts & terminals
Planning (all levels)Integration of operations & equipment typesAutomation
61© Teodor Gabriel Crainic 2006
Perspectives (3)
Carrier strategic & tactical planningMore studied than terminals, but Better representation/integration of “local” operations and characteristicsIntegration of employee scheduling impacts/relationsBetter representation of time dependenciesBetter integration of stochastic aspects into long-term planning modelsAlgorithmic developments
62© Teodor Gabriel Crainic 2006
Perspectives (4)
Short-term planningTime-dependent, stochastic formulations and algorithms Integrated models, e.g.,
Container fleet management over land and seaVehicles, power, crews, …
Modelling of ITS and e-logistics and integration to planning and management models; e.g.,
Flow of informationImpact on uncertainty
63© Teodor Gabriel Crainic 2006
Perspectives (5)
Modelling the impact of security measures and addressing the new issuesLogistic networks
Coordination & synchronizationInformation flows and uncertainties
MethodologyModels Methods exact and (meta) heuristicParallel computation