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A Memetic Algorithm for the Multi-Depot Vehicle Routing Problem with Limited Stocks

A Memetic Algorithm for the Multi-Depot Vehicle Routing Problem with Limited Stocks
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Author(s): Shi Li (Université de Technologie Belfort – Montbéliard, France)and Yahong Zheng (Wuhan University of Technology, China)
Copyright: 2015
Pages: 35
Source title: Handbook of Research on Artificial Intelligence Techniques and Algorithms
Source Author(s)/Editor(s): Pandian Vasant (University of Technology Petronas, Malaysia)
DOI: 10.4018/978-1-4666-7258-1.ch013

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Abstract

The Vehicle Routing Problem (VRP) is one of important combinatorial problems, which holds a central place in logistics management. One of the most widely studied problems in the VRP family is the Multi-Depot Vehicle Routing Problem (MDVRP), where more than one depot is considered. In this chapter, the authors focus on a new extension of the MDVRP in which goods loaded by the vehicle are restricted due to limited stocks available at warehouses. More specifically, this extension consists in determining a least cost routing plan that can satisfy all the customs demands by delivering available stocks. Indeed, this problem is often encountered when goods are shortage in some warehouses. To deal with the problem efficiently, a memetic algorithm is proposed in this chapter. The authors study this approach on a set of modified benchmark instances and compare its performance to a pure genetic algorithm.

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