Optimizing cut order planning in apparel production using evolutionary strategies

Wai Keung Wong, S. Y.S. Leung

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

3 Citations (Scopus)

Abstract

Cut order planning (COP) plays a significant role in managing the cost of materials. COP seeks to minimize the total manufacturing costs by developing feasible cutting order plans with respect to material, machine and labour. In this chapter, a genetic optimized decision-making model using adaptive evolutionary strategies is devised for COP. Four sets of real production data were collected to validate the proposed method. The experimental results demonstrate that the proposed method can reduce both the material costs and the production of additional garments while satisfying time constraints. Although the total operation time used is longer than that using industrial practice, this is outweighed by the benefits of reduction in fabric cost and extra garments.
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.
Pages81-105
Number of pages25
ISBN (Print)9780857097798
DOIs
Publication statusPublished - 1 Jan 2013

Keywords

  • Evolutionary strategies
  • Optimization
  • Resource utilization

ASJC Scopus subject areas

  • Engineering(all)

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