基于文化基因算法的多供应商多零售商VMI问题研究

doi:10.16731/j.cnki.1671-3133.2017.02.001

现代制造工程 ›› 2017, Vol. 437 ›› Issue (2): 1-7.doi: 10.16731/j.cnki.1671-3133.2017.02.001

• 试验研究 • 下一篇

基于文化基因算法的多供应商多零售商VMI问题研究

刘琳琳¹, 杨斌¹, 朱小林², 张志强³

1 上海海事大学科学研究院物流研究中心,上海 201306
2 上海海事大学文理学院,上海 201306
3 北京科技大学机械工程学院,北京 100083

收稿日期:2016-02-06 出版日期:2017-02-28 发布日期:2018-01-08
作者简介:刘琳琳,硕士研究生,主要研究方向为国际物流与跨国供应链管理
杨斌,研究院教授,主要研究方向为绿色物流、自贸区供应链
朱小林,副教授,主要研究方向为优化与统计建模
张志强,硕士研究生,主要研究方向为智能算法在调度问题中的应用
E-mail:smu_liulinlin@163.com
基金资助:
国家自然科学基金资助项目(71171129);上海市科委科研计划项目(12510501600;14DZ2280200;14511107402)

The research of multi-vendor multi-retailer VMI problem based on memetic algorithm

Liu Linlin¹, Yang Bin¹, Zhu Xiaolin², Zhang Zhiqiang³

1 Scientific Research Academy,Research Center of Logistics,Shanghai Maritime University,Shanghai 201306,China
2 College of Arts and Sciences,Shanghai Maritime University,Shanghai 201306,China
3 School of Mechanic Engineering,University of Science and Technology Beijing,Beijing 100083,China

Received:2016-02-06 Online:2017-02-28 Published:2018-01-08

摘要/Abstract

摘要： 针对多供应商-多零售商-单个中心仓库供应链背景下的供应商管理库存问题,考虑供应商、零售商以及中心仓库的订货量和订货频次的约束,构建了供应商管理库存问题总库存成本的数学模型;针对上述模型,采用文化基因算法进行求解,以总的库存成本最低为目标来求解供应商、零售商及中心仓库每年的订货频次和订货量。该算法将个体表示为VMI问题的解,建立问题和算法的映射关系;在全局搜索过程中,采用基于位置的交叉方式吸收最优个体的优秀基因;在局部搜索过程中,采用基于位置的变异方式产生一定规模的邻域基因个体。采用正交试验对算法的重要参数进行了优化配置,通过实例验证了算法的有效性。

关键词: 多供应商, 多零售商, 供应商管理库存, VMI, 文化基因算法, 供应链

Abstract: Under the background of multi-vendor multi-retailer single central warehouse supply chain,taking into account the constraints of the order quantities of the supplier,retailer,central warehouse,and the constrains of their order frequency,the total warehouse costs of vendor managed inventory problem mathematical model was established.To solve this model,aiming at the minimum total inventoy cost,memetic algorithm is used to solve the annual ordering frequency of the supplier,retailer,central warehouse,and the order quantity.An encoding way is built to bridge the VMI and the algorithm.In the process of global search,to absorb the genes of the best individual,use the crossover way that is based on the cross-way location.In the process of local search,to produce a certain scale neighborhood gene individuals,use the mutation way that is based on location.To get the best parameters of the algorithm,the orthogonal experimental design is used.The algorithm is used to solve a specific problem.The example shows the effectiveness of the algorithm.

Key words: multi-vendor, multi-retailer, vendor managed inventory, Vendor Management Inventory(VMI), memetic algorithm, supply chain

中图分类号:

TP391

刘琳琳, 杨斌, 朱小林, 张志强. 基于文化基因算法的多供应商多零售商VMI问题研究[J]. 现代制造工程, 2017, 437(2): 1-7.

Liu Linlin, Yang Bin, Zhu Xiaolin, Zhang Zhiqiang. The research of multi-vendor multi-retailer VMI problem based on memetic algorithm[J]. Modern Manufacturing Engineering, 2017, 437(2): 1-7.

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基于文化基因算法的多供应商多零售商VMI问题研究

The research of multi-vendor multi-retailer VMI problem based on memetic algorithm

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