Publication Type

Journal Article

Version

publishedVersion

Publication Date

8-2007

Abstract

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.

Keywords

Genetic algorithms, Cellular manufacturing, Cell formation, Group layout

Discipline

Numerical Analysis and Scientific Computing | Theory and Algorithms

Publication

European Journal of Operations Research

Volume

181

Issue

1

First Page

156

Last Page

167

ISSN

0377-2217

Identifier

10.1016/j.ejor.2006.05.035

Publisher

Elsevier

Copyright Owner and License

Publisher

Additional URL

https://doi.org/10.1016/j.ejor.2006.05.035

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