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不确定环境下的再制造闭环物流网络优化
引用本文:王振锋,崔岩,王亮,谢敏.不确定环境下的再制造闭环物流网络优化[J].计算机工程与应用,2012,48(36):221-226.
作者姓名:王振锋  崔岩  王亮  谢敏
作者单位:1. 河南农业大学机电工程学院,郑州,450002
2. 重庆大学机械工程学院,重庆,400030
基金项目:国家自然科学基金,河南省软科学研究计划项目
摘    要:考虑废旧产品回收数量、回收质量、再生产品需求量的不确定性以及废弃处理中心的选址等多重因素,构建单产品、多周期的再制造闭环物流网络优化设计模型,运用云遗传算法来确定物流网络中各设施的数量、位置、规模以及各设施间的合理物流分配量,使得在整个运营周期的净收益最大。通过算例来验证该模型的有效性。

关 键 词:再制造闭环物流网络  优化设计  云遗传算法  不确定环境

Optimization for remanufacturing closed-loop logistics network under uncertain environment
WANG Zhenfeng , CUI Yan , WANG Liang , XIE Min.Optimization for remanufacturing closed-loop logistics network under uncertain environment[J].Computer Engineering and Applications,2012,48(36):221-226.
Authors:WANG Zhenfeng  CUI Yan  WANG Liang  XIE Min
Affiliation:1.College of Mechanical and Electrical Engineering,Henan Agricultural University,Zhengzhou 450002,China 2.College of Mechanical Engineering,Chongqing University,Chongqing 400030,China
Abstract:Considering the uncertainty of the recoverable quantities, quality of used products, the demanded quantities of remanufactured products and the site of waste production treatment center, a single-commodity, multi-period optimization model for remanufacturing closed-loop logistics network is proposed. Cloud genetic algorithm is applied to deciding upon the number and scale of various facilities, their locations and the allocation of the corresponding goods flows, so that the net revenue is maximum at the end of entire operating cycle. The validity of the model is demonstrated through an example.
Keywords:remanufacturing closed-loop logistics network  optimization design  cloud genetic algorithm  uncertain environment
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