Skip to main content

Multi-objective optimization of manufacturing cell design

Buy Article:

$55.00 plus tax (Refund Policy)

Whereas the single-objective cell-formation problem has been studied extensively during the past decades, research on the multi-objective version of the problem has been relatively limited, despite the fact that it represents a more realistic modelling of the manufacturing environment. This article introduces multi-objective GP-SLCA, an evolutionary computation methodology for the solution of the multi-objective cell-formation problem. GP-SLCA is a hybrid algorithm, comprising of GP-SLCA, a genetic programming algorithm for the solution of single-objective cell-formation problems, and NSGA-II, a standard evolutionary multi-objective optimization technique. The proposed methodology is capable of providing the decision maker with a range of non-dominated solutions instead of a single compromise solution, which is usually produced as an outcome of alternative multi-objective optimization techniques. The application of multi-objective GP-SLCA is illustrated on a large-sized test problem taken from the literature.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Cell-formation problem; Cellular manufacturing; Evolutionary computation; Genetic programming; Multi-objective optimization; NSGA-II

Document Type: Research Article

Affiliations: School of Computer Science and Engineering, Cyprus College, 6 Diogenous Street, Engomi, P.O. Box 22006, 1516 Nicosia, Cyprus

Publication date: 2006-11-15

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more