Ant Colony Algorithm for Two Stage Supply Chain

Ant Colony Algorithm for Two Stage Supply Chain

R. Sridharan, Vinay V. Panicker
Copyright: © 2014 |Pages: 13
DOI: 10.4018/978-1-4666-5202-6.ch015
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Abstract

This chapter focuses on the distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The supply chain considered in this research consists of suppliers, distributors and customers. Each transportation route is associated with a fixed charge (or a fixed cost) and a transportation cost per unit transported. The presence of this fixed cost makes the problem difficult to solve. This motivates the researchers to develop heuristics based on non-traditional optimization techniques that can provide near-optimal solutions in reasonable time. In this research, an ant colony optimization based heuristic is proposed to solve a distribution-allocation problem with fixed cost for transportation routes in a two-stage supply chain. The comparative analysis carried out in this study reveals that the solutions obtained using proposed heuristic are better than those obtained using an existing heuristic in terms of total cost and computational time. In addition, special emphasis is placed in developing heuristics based on ant colony optimization for solving supply chain related problems and identifying opportunities for further research in this area.
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Main Focus Of The Chapter

Distribution-Allocation Problem

This work deals with modeling and analysis of the distribution-allocation problem in a two-stage supply chain with a fixed charge for a transportation route. The model considers a two-stage supply chain consisting of m suppliers, d distribution centers and n customers. The objective of the problem is to allocate the customers to the distribution centers and the distribution centers to the suppliers, minimizing the total cost of supply chain operation. In this chapter, an ACO-based heuristic has been developed.

Recently, Jawahar and Balaji (2009) propose a two-stage distribution-allocation model in a supply chain with a fixed cost for a transportation route. GA-based heuristic is proposed for solving the model. A matrix-based representation is used to code a candidate solution in the proposed GA-based heuristic. The same researchers present a simulated annealing-based heuristic for solving a two-stage FCTP in Balaji and Jawahar (2010). Later, Panicker, Vanga and Sridharan (2013) develop an ACO-based heuristic for solving a distribution-allocation problem in a two-stage supply chain.

Key Terms in this Chapter

Distribution Centers: Facilities where products are received, sorted, stored, and shipped to the destination.

Level of Significance: The probability of rejecting the null hypothesis in a statistical test when it is true.

Algorithm: A specific mathematical process for computation, following a set of rules for solving a problem in a finite number of steps.

Distribution: The activities associated with the physical movement of finished goods or service parts, from the manufacturer to the customer. These activities involve the functions of transportation, warehousing, inventory control, material handling, order processing, packaging, data processing, and communication for effective management.

Mathematical Model: An abstract representation of the real-world system using mathematical concepts.

Random Number: A number chosen using a random sampling from a random number table or generated by a computer.

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