Effective selection and allocation of material handling equipment for stochastic production material demand problems using genetic algorithm

T. C. Poon, King Lun Tommy Choy, C. K. Cheng, S. I. Lao, H. Y. Lam

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)

Abstract

This paper addresses the stochastic production demand problem in a manufacturing company. The objective of this research is to minimize the waiting time of production workstations and reduce stochastic production material problems through coordinating pickup and delivery orders in a warehouse. RFID technology is adopted to visualize the actual status of operations in production and warehouse environments. A mathematical model is developed to address this problem and a meta-heuristic algorithm using genetic algorithm (GA) is also developed to improve performance. Computational experiments are undertaken to examine the performance of the algorithm when dealing with congestion in cases of heavy and normal demand for production material. The overall result shows that the algorithm efficiently minimizes the total makespan of the production shop floor.
Original languageEnglish
Pages (from-to)12497-12505
Number of pages9
JournalExpert Systems with Applications
Volume38
Issue number10
DOIs
Publication statusPublished - 15 Sep 2011

Keywords

  • GA
  • RFID
  • Stochastic production demand problem

ASJC Scopus subject areas

  • Engineering(all)
  • Computer Science Applications
  • Artificial Intelligence

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