A Genetic Algorithm for Vehicle Routing Problems with Mixed Delivery and Pick-up

Department of Industrial Engineering, College of Advanced Technology, Kyung Hee University, Yongin, 449-701Most industrial logistic systems have focused on carrying products from manufacturers or distribution centers to customers. In recent years, they are faced with the problem of integrating reverse flows into their transportation systems. In this paper, we address the vehicle routing problems with mixed delivery and pick-up(VRPMDP). Mixed operation of delivery and pick-up during a vehicle tour requires rearrangement of the goods on board. The VRPMDP considers the reshuffling time of goods at customers, hard time windows, and split operation of delivery and pick-up. We construct a mixed integer mathematical model and propose a new genetic algorithm named GAMP for VRPMDP. Computational experiments on various types of test problems are performed to evaluate GAMP against the modified DethloffNs algorithm. The results show that GAMP reduces the total vehicle operation time by 5.9% on average, but takes about six times longer computation time. Keywords : genetic algorithm, vehicle routing problems, mixed de livery and pick-up, time windows, reverse logistics

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