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An Improved Genetic Algorithm for the Vehicle Routing Problem with Simultaneous Delivery and Pick-up Service

机译:同时配送和接送服务的车辆路径问题的改进遗传算法

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The vehicle routing problem with simultaneous deliver)' and pick-up (VRP-SDP) is a variant of the classical vehicle routing problem (VRP) where clients require simultaneous delivery and pick-up. Deliveries are supplied from a single depot at the beginning of the vehicle's service, while pick-up loads are taken to the same depot at the conclusion of the service. One important characteristic of this problem is that a vehicle's load in any given route is a mix of delivery and pick-up loads, at the same time in any route the vehicle can not violate some constraints ,for example (he vehicle capacity and traveling distance constraints.In this paper, VRP-SDP was introduced and described from the point of view that combines the logistics and reverse logistics (bidirectional logistics), we constructed a universal integer programming mathemattc model of VRP-SDP in detail, which can transform into other classical vehicle routing problems by setting different parameters. Meantime, an improved genetic algorithm (IGA) was proposed to overcome the shortcomings of premature convergence and slow convergence of conventional genetic algorithm (GA). The novel crossover-operator, swapping operator and inversion operator as the core of IGA were constructed to solve VRP-SDP. We compared the performance of the proposed IGA with GA. The experiment results show that the performance of IGA is better than GA.
机译:具有同时交付和提货(VRP-SDP)的车辆路线问题是经典车辆路线问题(VRP)的一种变体,客户需要同时交付和提货。车辆服务开始时,从单个仓库提供货物,服务结束时将取货装载到同一仓库。这个问题的一个重要特征是,任何给定路线上的车辆负载都是运输和提货负载的混合,同时,在任何路线上,车辆都不能违反某些约束条件,例如(车辆容量和行驶距离)本文从结合物流和逆向物流(双向物流)的角度介绍和描述了VRP-SDP,我们详细构建了VRP-SDP的通用整数规划数学模型,可以将其转化为其他约束。通过设置不同的参数来解决经典车辆路径问题,同时提出了一种改进的遗传算法(IGA),克服了传统遗传算法(GA)过早收敛和收敛慢的缺点,提出了一种新型的交叉算子,交换算子和反算子。构造了IGA的核心以解决VRP-SDP问题,将所提出的IGA与GA的性能进行了比较,实验结果表明: IGA的性能优于GA。

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