Solving the multi-buyer joint replenishment problem with a modified genetic algorithm

被引：28

作者：

Chan, CK

Cheung, BKS

Langevin, A

机构：

[1] Ecole Hautes Etud Commerciales, Gerad, Montreal, PQ H3C 3A7, Canada

[2] Ecole Polytech, Dept Math & Genie Ind, Montreal, PQ H3C 3A7, Canada

[3] Hong Kong Polytech Univ, Dept Math Appl, Hong Kong, Hong Kong, Peoples R China

来源：

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL | 2003年 / 37卷 / 03期

关键词：

joint replenishment problem; genetic algorithm; inventory; multi-buyer; heuristics;

D O I：

10.1016/S0191-2615(02)00015-2

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

The joint replenishment problem (JRP) is a multi-item inventory problem. The objective is to develop inventory policies that minimize the total costs (comprised of holding cost and setup cost) over the planning horizon. In this paper, we look at the multi-buyer, multi-item version of the JRP. We propose a new modified genetic algorithm which is very efficient. Tests are conducted on problems from a leading bank in Hong Kong and from the literature. (C) 2003 Elsevier Science Ltd. All rights reserved.

引用

页码：291 / 299

页数：9

共 13 条

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