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Development of a hybrid genetic algorithm to solve the multi-depot vehicle routing problem

Pratikakis Charidimos

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Year 2017
Type of Item Diploma Work
Bibliographic Citation Charidimos Pratikakis, "Development of a hybrid genetic algorithm to solve the multi-depot vehicle routing problem", Diploma Work, School of Production Engineering and Management, Technical University of Crete, Chania, Greece, 2017
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The distribution of finished products from depots to customers is a practical and challenging problem in logistics management. Better routing and scheduling decisions can result in higher level of customer satisfaction because more customers can be served in a shorter time.The distribution problem is generally formulated as the vehicle routing problem (VRP). Nevertheless, there is a rigid assumption that there is only one depot. In cases, for instance, where a logistics company has more than one depot, the VRP is not suitable. To resolve this limitation, this paper focuses on the VRP with multiple depots, or multi-depot VRP (MDVRP).The MDVRP is NP-hard, which means that an efficient algorithm for solving the problem optimally is unavailable.During the course of this paper, a hybrid genetic algorithm is developed, that makes use of the Clarke and Wright Savings method as well as the nearest neighbor heuristic, for the solution of the above problem. The performance of the proposed algorithm is tested by carrying out computational studies in a wide range of problems. Lastly, the results obtained from the proposed algorithm are compared against benchmark data and suggestions for further improvement of the algorithm as well as ideas for future work are given.

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