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A Pseudo-Parallel Genetic Algorithm Integrating Simulated Annealing for Stochastic Location-Inventory-Routing Problem with Consideration of Returns in E-Commerce

机译:考虑到电子商务回报的随机地点清点问题模拟退​​火的伪平行遗传算法

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摘要

Facility location, inventory control, and vehicle routes scheduling are three key issues to be settled in the design of logistics system for e-commerce. Due to the online shopping features of e-commerce, customer returns are becoming much more than traditional commerce. This paper studies a three-phase supply chain distribution system consisting of one supplier, a set of retailers, and a single type of product with continuous review (Q, r) inventory policy. We formulate a stochastic location-inventory-routing problem (LIRP) model with no quality defects returns. To solve the NP-hand problem, a pseudo-parallel genetic algorithm integrating simulated annealing (PPGASA) is proposed. The computational results show that PPGASA outperforms GA on optimal solution, computing time, and computing stability.
机译:设施位置,库存控制和车辆路线调度是在电子商务的物流系统设计中解决的三个关键问题。由于电子商务的在线购物特征,客户回报变得远远超过传统的商业。本文研究了一个由一个供应商,一组零售商和单一类型产品组成的三相供应链分布系统,以及连续评审(Q,R)库存政策。我们制定了一个随机地点库存路由问题(LIRP)模型,没有质量缺陷返回。为了解决NP手问题,提出了一种积分模拟退火(PPGASA)的伪并行遗传算法。计算结果表明,PPGASA在最佳解决方案,计算时间和计算稳定性上优于GA。

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