Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and fuzzy set theory

Pik Yin Mok, Chun Kit Kwong, Wai Keung Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

45 Citations (Scopus)

Abstract

In apparel industry, manufacturers developed standard allowed minutes (SAMs) databases on various manufacturing operations in order to facilitate better scheduling, while effective production schedules ensure smoothness of downstream operations. As apparel manufacturing environment is fuzzy and dynamic, rigid production schedules based on SAMs become futile in the presence of any uncertainty. In this paper, a fuzzification scheme is proposed to fuzzify the static standard time so as to incorporate some uncertainties, in terms of both job-specific and human related factors, into the fabric-cutting scheduling problem. A genetic optimisation procedure is also proposed to search for fault-tolerant schedules using genetic algorithms, such that makespan and scheduling uncertainties are minimised. Two sets of real production data were collected to validate the proposed method. Experimental results indicate that the genetically optimised fault-tolerant schedules not only improve the operation performance but also minimise the scheduling risks.
Original languageEnglish
Pages (from-to)1876-1893
Number of pages18
JournalEuropean Journal of Operational Research
Volume177
Issue number3
DOIs
Publication statusPublished - 16 Mar 2007

Keywords

  • Fabric cutting
  • Fuzzy set theory
  • Genetic algorithms
  • Parallel machine scheduling

ASJC Scopus subject areas

  • Information Systems and Management
  • Management Science and Operations Research
  • Statistics, Probability and Uncertainty
  • Applied Mathematics
  • Modelling and Simulation
  • Transportation

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