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Network site optimization of reverse logistics for E-commerce based on genetic algorithm

机译:基于遗传算法的电子商务逆向物流网站优化

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摘要

Product returns have been viewed as an unavoidable cost for online sales, forfeiting any chance of cost savings. As competition pressure continues to mount in E-commerce, B2B or B2C, E-commerce corporations have begun to explore the possibility of managing product returns in a more cost-efficient manner by rescheduling the locations of recycling centers. However, few studies have addressed the problem of optimization of the numbers and location of collecting points, recycling centers and remanufacturing centers for E-commerce based on genetic algorithm. To fill the void in such a line of research, this paper proposes a genetic algorithm-based model that can solve the location-allocation optimization of reverse logistics for E-commerce. The usefulness of the proposed model and algorithm was validated by its application to an illustrative example dealing with logistics sites allocation from online sales.
机译:产品退货被视为在线销售不可避免的成本,从而丧失了节省成本的任何机会。随着电子商务,B2B或B2C的竞争压力持续加剧,电子商务公司已开始探索通过重新安排回收中心的位置来以更具成本效益的方式管理产品退货的可能性。然而,很少有研究解决基于遗传算法的电子商务的收集点,回收中心和再制造中心的数量和位置的优化问题。为了填补这一研究空白,本文提出了一种基于遗传算法的模型,可以解决电子商务逆向物流的位置分配优化问题。通过将其应用于处理来自在线销售的物流站点分配的示例性示例,验证了所提出模型和算法的有效性。

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