Bi-objective optimization of supply chain usingLingo and NSGA II

Submitted by Nerella Arudhra

Submitted toGIBS, Delhi

Objectives

1. Identification of various operations taking place in warehouse.

2. Maximization selection of suitable supplier

3. minimization of total transportation cost throughout the supply chain

Introduction

• Recent advancement of technology and cultural changes are influencing the supply chain design.

• Logistics industry in India is an industry that has not achieved its much deserved attention or recognition.

• the Indian economy along with the influx of new companies in sectors that was otherwise unknown.

• Estimated at a value of $14 billion US dollars this industry is slated for another 9% to 10% growth in the years to come.

• Supplier selection is an important concern of a firm’s competitiveness, more so in the context of the imperative of supply-chain management.

Different tires of logistics include• 1PL – Shipper

• 2PL – Traditional Transportation Provider

• 3PL – Integrated Logistics Service Provider

• Out sourcing of logistics services that are to be performed in house of the organization. Where 3PL is gaining more importance in India as logistics being emerging business.

• 4PL – High Level Logistics/IT Consulting

• The consulting service which integrates technology, capabilities and resources of own organization with other organization to design, build and run comprehensive supply chain solutions.

• 5PL – Consulting for the High Level Logistics/IT Consultants

• 6PL – Artificial Intelligence Driven Supply Chain Management

• 7PL – Autonomous Competitor Created to Test Alternative Supply Chain Strategies

• 8PL – Super Committee Created to Analyze Competitor’s Results

• 9PL – Crowd Sourced Managed Logistics Strategy

• 10PL – Supply Chain Becomes Self Aware and Runs Itself

Supply Chain – Safexpress Indore warehouse

Warehouse operations

1 – 6: Local Delivery 39 – 41: 3PL

7 – 38: Fast Lane area 42 – 46: FTL (Transoultion)

Booking of Consignment

Receiving order details and

conformationTran

sship

men

t

Transsh

ipm

ent

Customer Request

ViaPhone, email,

portal, EDI (Electronic Data

Interface)

TransshipmentYesAcceptance

Rejected

Pick up of freight

Delivering to Respective HUB/ Dock

Local Booking Office (Consolidation, Packaging,

Documentation, etc.)

Delivering to Respective HUB/ Dock

Notification of Terms & condition; Taking note of

necessary details

(No.of Packages; Weight; Special Instructions)

Route PlanTaking Vehicle To Customer

Booking Kit usageDeclaration

Remain documents (Invoice, etc.…)Packing Checking

Loading into Vehicle

Problem Discerption

1 1 1

1

objective function

1 (1)

2 * * (2)

subjected to constraints

1

n n n

i i i i i i

i i i

SJ SJ JI JI

S J J I

n

i

i

f PX Q X D X

f T Q C Q

X

1

(3)

(4)

i = 1,2.........n (5)

i = 1,2.........n

n

i

i

i i i

i i i

Y h

X U Y

X l Y

(6)

0 i = 1,2.........n (7)

0,1 i = 1,2.........n (8)

(9)

i

i

SJ JI

S

SJ

X

Y

Q Q J

Q SUP

S (10)S

J

Maximization of supplier selection

Minimization of transportation cost

Total order of supplier is varied

Supplier is in the portfolio

Classical NSGA II algorithm

• we considered a multi-objective NSGA-II togenerate optimal solutions.

• As NSGA differs fromwell-known simple geneticalgorithm is only in the waythe selection operatorworks.

Lingo

• LINGO is a simple tool for utilizing the power of linear and nonlinearoptimization to formulate large problems concisely, solve them, and analyze thesolution.

• Optimization problems are often classified as linear or nonlinear, depending onwhether the relationships in the problem are linear with respect to the variables.

Lingo

Results and discussion - Lingo

Results and discussion – NSGA II (MATLAB)

The Pareto optimal solutions of theconsidered two performancemeasures such as supplier selectionand transportation cost with theclassical NSGA-II

Conclusion and future work

• In this era of crumbling economic barriers, the customer reigns supreme. The focustoday is not on meeting the customer’s expectations, but on exceeding them.

•

• The strategic role of logistics and supply chain management in this regard becomes vital.

• There have been changes in the logistics organizational structure from being a part ofvarious functions like manufacturing, finance, and marketing to a core function.

•

• Further work may include generation of hybrid algorithms to solve on more problemswith many performance measures that affect the system.

• Therefore considering the GST on logistics and including environmental concern factorsin the objective function.

Suggestions

• Usage of 4 way pallet for the better movement of pallet along the bay and usage of

worker effectively.

• Recognition of pallet to the suitable destination bay (i.e. each bay is allocated to

particular city with a particular strategy) with the color coding of pallet and

boarding. This makes easy understanding for the worker.

• Suggest proper analytical tools for enriching of data, including and planning the

future objectives that decreases the carbon foot print.

References

• Farahani, Reza Zanjirani, and Mahsa Elahipanah. "A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain." International Journal of Production Economics 111.2 (2008): 229-243.

• Yeh, Wei-Chang, and Mei-Chi Chuang. "Using multi-objective genetic algorithm for partner selection in green supply chain problems." Expert Systems with applications 38.4 (2011): 4244-4253.

• Amodeo, Lionel, Haoxun Chen, and Aboubacar El Hadji. "Multi-objective supply chain optimization: An industrial case study." Workshops on Applications of Evolutionary Computation. Springer Berlin Heidelberg, 2007.

• Serrano, Víctor, Matías Alvarado, and Carlos A. Coello Coello. "Optimization to manage supply chain disruptions using the NSGA-II." Theoretical Advances and Applications of Fuzzy Logic and Soft Computing. Springer Berlin Heidelberg, 2007. 476-485.

• Srivastava, Samir K. "Logistics and supply chain practices in India." Vision: The Journal of Business Perspective 10.3 (2006): 69-79.

• Adhikary, Anindita, and Bedanta Bora. "Supply Chain Challenges in India: An Empirical Insight." The International Journal of Business & Management 2.4 (2014): 31.