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

Chi Kin Chan, Bernard K.S. Cheung, André Langevin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

36 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)291-299
Number of pages9
JournalTransportation Research Part B: Methodological
Volume37
Issue number3
DOIs
Publication statusPublished - 1 Jan 2003

Keywords

  • Genetic algorithm
  • Heuristics
  • Inventory
  • Joint replenishment problem
  • Multi-buyer

ASJC Scopus subject areas

  • Transportation
  • Management Science and Operations Research

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