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A mixed integer linear programming model for the vehicle routing problem with simultaneous delivery and pickup by heterogeneous vehicles, and constrained by time windows

机译:混合整数线性规划模型,用于车辆路径问题,其中异类车辆同时交付和提取,并且受时间窗口约束

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In this work, we consider the Vehicle Routing Problem with Simultaneous Delivery and Pickup, and constrained by time windows, to improve the performance and responsiveness of the supply chain by transporting goods from one location to another location in an efficient manner. In this class of problem, each customer demands a quantity to be delivered as a part of the forward supply service and another quantity to be picked up as a part of the reverse recycling service, and the complete service has to be done simultaneously in a single visit of a vehicle, and the objective is to minimize the total cost, which includes the traveling cost anddispatching cost for operating vehicles. We propose a Mixed Integer Linear Programming (MILP) model for solving this class of problem. In order to evaluate the performance of the proposed MILP model, a comparison study is made between the proposed MILP model and an existing MILP model available in the literature, with the consideration of heterogeneous vehicles. Our study indicates that the proposed MILP model gives tighter lower bound and also performs better in terms of the execution time to solve each of the randomly generatedproblem instances, in comparison with the existing MILP model. In addition, we also compare the proposed MILP model (assuming homogeneous vehicles) with the existing MILP model that also considers homogeneous vehicles. The results of the computational evaluation indicate that the proposed MILP model gives much tighter lower bound, and it is competitive to the existing MILP model in terms of the execution time to solve each of the randomly generated problem instances.
机译:在这项工作中,我们考虑了具有同时交付和提取的车辆路径问题,并受时间窗口的约束,以通过有效地将货物从一个地点运输到另一个地点来改善供应链的性能和响应能力。在此类问题中,每个客户都要求将一个数量的货物作为正向供应服务的一部分交付,并要求另一个数量的货物作为反向回收服务的一部分进行提取,而完整的服务必须在单个流程中同时完成造访车辆,目的是使总成本降到最低,其中包括行驶成本和运营车辆的调度成本。我们提出了混合整数线性规划(MILP)模型来解决此类问题。为了评估拟议的MILP模型的性能,在考虑异构车辆的情况下,对拟议的MILP模型与文献中现有的MILP模型进行了比较研究。我们的研究表明,与现有的MILP模型相比,拟议的MILP模型给出了更严格的下界,并且在解决每个随机生成的问题实例的执行时间方面也表现更好。此外,我们还将提议的MILP模型(假设同质车辆)与也考虑同质车辆的现有MILP模型进行了比较。计算评估的结果表明,提出的MILP模型给出了更严格的下限,并且在解决每个随机生成的问题实例的执行时间方面,与现有的MILP模型相比具有竞争力。

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