Title

An Evolutionary Fuzzy Multi-Objective Approach to Cell Formation

Publication Type

Conference Proceeding Article

Publication Date

5-2006

Abstract

Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applications because it can only be used to solve small-size problems. In this paper, we propose a heuristic genetic algorithm (HGA) as a viable solution for solving large-scale fuzzy multi-objective CF problems. Heuristic crossover and mutation operators are developed to improve computational efficiency. Our results show that the HGA outperforms the FMP and goal programming (GP) models in terms of clustering results, computational time, and user friendliness.

Discipline

Computer Sciences | Management Information Systems

Research Areas

Information Systems and Management; Intelligent Systems and Decision Analytics

Publication

Simulated Evolution and Learning: 6th International Conference, SEAL 2006, Hefei, China, October 15-18, 2006. Proceedings

Volume

4247

First Page

377

Last Page

383

ISBN

9783540473312

Identifier

10.1007/11903697_48

Publisher

Springer Verlag

City or Country

Hefei, China

Additional URL

http://dx.doi.org/10.1007/11903697_48