A genetic algorithm for cellular manufacturing design and layout

Xiaodan Wu, Chao Hsien Chu, Yunfeng Wang, Weili Yan

Research output: Contribution to journalArticlepeer-review

171 Scopus citations


Cellular manufacturing (CM) is an approach that can be used to enhance both flexibility and efficiency in today's small-to-medium lot production environment. The design of a CM system (CMS) often involves three major decisions: cell formation, group layout, and group schedule. Ideally, these decisions should be addressed simultaneously in order to obtain the best results. However, due to the complexity and NP-complete nature of each decision and the limitations of traditional approaches, most researchers have only addressed these decisions sequentially or independently. In this study, a hierarchical genetic algorithm is developed to simultaneously form manufacturing cells and determine the group layout of a CMS. The intrinsic features of our proposed algorithm include a hierarchical chromosome structure to encode two important cell design decisions, a new selection scheme to dynamically consider two correlated fitness functions, and a group mutation operator to increase the probability of mutation. From the computational analyses, these proposed structure and operators are found to be effective in improving solution quality as well as accelerating convergence.

Original languageEnglish (US)
Pages (from-to)156-167
Number of pages12
JournalEuropean Journal of Operational Research
Issue number1
StatePublished - Aug 16 2007

All Science Journal Classification (ASJC) codes

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research
  • Information Systems and Management


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