Scheduling different types of vehicles in distribution centers with fixed due dates and packed shipments

Abstract

This paper proposes a novel non-dominated sorting genetic algorithm-based method for scheduling simultaneously different types of vehicles with different capacities in distribution centers working as cross dock. In this paper, a three-objective model is proposed, which minimizes operational time, lateness and earliness of delivering products.In many of real life cases, packs of products with different number of products must be unloaded instead of arbitrary number of products because of products’ nature and/or physical limitations. It means that the optional amount of unloading is not prohibited in many of real life cases unlike to previous researches; therefore, scheduling vehicles by considering this limitation is different from previous works that allow optional amount of unloading.Another advantage of this paper is consideration of the frequent unloading pattern of inbound vehicles. This consideration better synchronizes the inbound and outbound vehicles compared to non-frequent pattern, and as a result, it helps to reduce the operational time of cross docking as well as the shipping cycle.This paper proposes a new scheduling method for considering the mentioned novelties. Furthermore, Taguchi design is used for regulating the proposed algorithm’s parameters. Several numerical examples are solved by the proposed method, and the obtained results are compared to multi-objective particle swarm optimization. The numerical results show the superiority of the proposed method.