Determining the optimal number of Kanban in multi-products supply chain system

G. A. Widyadana, H. M. Wee, Jer Yuan Chang

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

Kanban, a key element of just-in-time system, is a re-order card or signboard giving instruction or triggering the pull system to manufacture or supply a component based on actual usage of material. There are two types of Kanban: production Kanban and withdrawal Kanban. This study uses optimal and meta-heuristic methods to determine the Kanban quantity and withdrawal lot sizes in a supply chain system. Although the mix integer programming method gives an optimal solution, it is not time efficient. For this reason, the meta-heuristic methods are suggested. In this study, a genetic algorithm (GA) and a hybrid of genetic algorithm and simulated annealing (GASA) are used. The study compares the performance of GA and GASA with that of the optimal method using MIP. The given problems show that both GA and GASA result in a near optimal solution, and they outdo the optimal method in term of run time. In addition, the GASA heuristic method gives a better performance than the GA heuristic method.

Original languageEnglish
Pages (from-to)189-201
Number of pages13
JournalInternational Journal of Systems Science
Volume41
Issue number2
DOIs
Publication statusPublished - Feb 2010
Externally publishedYes

Keywords

  • Genetic algorithm
  • Kanban
  • Mix integer programming
  • Multi-product supply chain
  • Simulated annealing

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