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首页> 外文期刊>Journal of the Operational Research Society >A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service
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A genetic-algorithm-based approach to the two-echelon capacitated vehicle routing problem with stochastic demands in logistics service

机译：基于遗传算法的物流服务中随机需求的二级梯级车辆路径问题

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摘要

This paper addresses the two-echelon capacitated vehicle routing problem (2E-CVRP) with stochastic demands (2E-CVRPSD) in city logistics. A stochastic program with recourse is used to describe the problem. This program aims to minimize the sum of the travel cost and the expected cost of recourse actions resulting from potential route failures. In a two-echelon distribution system, split deliveries are allowed at the first level but not at the second level, thereby increasing the difficulty of calculating the expected failure cost. Three types of routes with or without split deliveries are identified. Different methods are devised or adapted from the literature to compute the failure cost. A genetic-algorithm-based (GA) approach is proposed to solve the 2E-CVRPSD. A simple encoding and decoding scheme, a modified route copy crossover operator, and a satellite-selection-based mutation operator are devised in this approach. The numerical results show that for all instances, the expected cost of the best 2E-CVRPSD solution found by the proposed approach is not greater than that of the best-known 2E-CVRP solution with an average relative gap of 2.57%. Therefore, the GA-based approach can find high-quality solutions for the 2E-CVRPSD.
机译：本文针对具有随机需求（2E-CVRPSD）的城市物流中的两级容量车辆路径问题（2E-CVRP）。带有追索权的随机程序用于描述问题。该计划旨在最大程度地减少行程成本和潜在路线故障导致的补救措施预期成本之和。在两级分配系统中，允许在第一级而不是第二级进行拆分交付，从而增加了计算预期故障成本的难度。确定了三种类型的有或没有分开交付的路线。从文献中设计或采用了不同的方法来计算故障成本。提出了一种基于遗传算法的遗传算法来解决2E-CVRPSD问题。用这种方法设计了一种简单的编码和解码方案，一个经过修改的路由复制交叉算子和一个基于卫星选择的变异算子。数值结果表明，在所有情况下，通过该方法发现的最佳2E-CVRPSD解决方案的预期成本不大于平均相对差距为2.57％的最佳2E-CVRP解决方案的预期成本。因此，基于GA的方法可以找到2E-CVRPSD的高质量解决方案。

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