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一种用于电子供应链环境下考虑退货的选址-库存-路径问题的混合遗传-模拟退火算法。

A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment.

作者信息

Li Yanhui, Guo Hao, Wang Lin, Fu Jing

机构信息

School of Information Management, Central China Normal University, Wuhan 430079, China.

School of Management, Huazhong University of Science and Technology, Wuhan 430074, China.

出版信息

ScientificWorldJournal. 2013 Dec 29;2013:125893. doi: 10.1155/2013/125893. eCollection 2013.

Abstract

Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.

摘要

设施选址、库存控制和车辆路线调度是电子商务物流系统设计中的关键且高度相关的问题。同时,网络销售中的退货率显著高于传统商业。许多退货商品没有质量缺陷,经过简单的重新包装过程后即可重新进入销售渠道。针对电子商务物流系统中存在的问题,我们构建了一个考虑无质量缺陷退货的选址 - 库存 - 路线问题模型。为解决这个NP难问题,提出了一种有效的混合遗传模拟退火算法(HGSAA)。数值算例结果表明,HGSAA在计算时间、最优解和计算稳定性方面均优于遗传算法(GA)。所提出的模型对于帮助管理者在电子供应链环境下做出正确决策非常有用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a4a/3891439/1f24b48add41/TSWJ2013-125893.alg.001.jpg

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