遗传算法在逆向物流网络选址问题中的应用研究

A Genetic Algorithm Approach to Location-Allocation Problem in Reverse Logistic Network

随着公众环保意识的增强、环保立法的出台和可观的经济利益的显现 ,企业开始关注逆向物流。而在逆向物流中 ,集中退货中心管理是企业逆向物流系统高品质运作的基础和前提。因此 ,本文构建了一个逆向物流网络中的选址模型 ,旨在研究从备选地址中选择建立配送中心或回收中心最佳策略 ,然后应用遗传算法讨论了该模型的具体解法。最后针对模拟算例 ,通过对比遗传算法和部分枚举法的效率及结果 。

Driven by growing environmental concern,legislative regulation and economic profitability,manufactures concern more and more about the physical design of the reverse logistic network,which is a problem belonging to a class of facility-location problems.This paper develops a capacitated location-allocation model with reverse logistics to find the location and capacity of return centers and distribution centers.Efficient GA is developed to solve the problem,compared with partly enumerated method.