Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/10924
Title: Solving the multi-buyer joint replenishment problem with a modified genetic algorithm
Authors: Chan, CK 
Cheung, BKS
Langevin, A
Keywords: Genetic algorithm
Heuristics
Inventory
Joint replenishment problem
Multi-buyer
Issue Date: 2003
Publisher: Pergamon Press
Source: Transportation research. Part B, Methodological, 2003, v. 37, no. 3, p. 291-299 How to cite?
Journal: Transportation research. Part B, Methodological 
Abstract: 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.
URI: http://hdl.handle.net/10397/10924
ISSN: 0191-2615
EISSN: 1879-2367
DOI: 10.1016/S0191-2615(02)00015-2
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