Optimizing apparel production systems using genetic algorithms

Wai Keung Wong, Pik Yin Mok, S. Y.S. Leung

Research output: Chapter in book / Conference proceedingChapter in an edited book (as author)Academic researchpeer-review

3 Citations (Scopus)

Abstract

In apparel manufacturing, it is difficult to achieve line balance because the production rate of each workstation is different. This difficulty is particularly prominent in a labour-intensive assembly process. The development of a line balancing technique using genetic algorithms is thus proposed for optimizing the assignment of operatives in an assembly line. The impact of different levels of skill inventory SInon the assembly makespan is also investigated in order to find out the optimal number of task skills an operative should possess in the apparel assembly process. Experimental results will be discussed to demonstrate the performance of the proposed genetic optimization approach.
Original languageEnglish
Title of host publicationOptimizing Decision Making in the Apparel Supply Chain Using Artificial Intelligence (AI)
Subtitle of host publicationFrom Production to Retail
PublisherElsevier Inc.
Pages153-169
Number of pages17
ISBN (Print)9780857097798
DOIs
Publication statusPublished - 1 Jan 2013

Keywords

  • Apparel manufacture
  • Genetic algorithms
  • Line balance
  • Optimization

ASJC Scopus subject areas

  • Engineering(all)

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