Genetic algorithms for integrating cell formation with machine layout and scheduling

Xiaodan Wu, Chao Hsien Chu, Yunfeng Wang, Dianmin Yue

Research output: Contribution to journalArticlepeer-review

78 Scopus citations

Abstract

Cellular manufacturing (CM) has been recognized as an innovative practice for companies to gain efficiency as well as flexibility under today's small-to-medium lot and customization-oriented manufacturing environment. Among the necessary decisions for a successful CM implementation, cell formation (CF), group layout (GL) and group scheduling (GS) are the three most popular ones. These decisions are interrelated and may impact each other but they are often treated separately or as a sequential decision in prior research. In this paper, we propose a new approach to concurrently make the CF, GL and GS decisions. A conceptual framework and mathematical model, which integrates these decisions, are proposed. A hierarchical genetic algorithm (HGA) is developed to solve the integrated cell design problem. Two heuristic operators are proposed to enhance its computational performance. The results from our study indicate that: (1) the concurrent approach often found better solutions than the sequential one, and (2) with the proposed heuristic operators, the HGA procedure performed better than without them.

Original languageEnglish (US)
Pages (from-to)277-289
Number of pages13
JournalComputers and Industrial Engineering
Volume53
Issue number2
DOIs
StatePublished - Sep 2007

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

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