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Journal of Applied Sciences
  Year: 2008 | Volume: 8 | Issue: 18 | Page No.: 3199-3206
DOI: 10.3923/jas.2008.3199.3206
 
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A Methodology for Optimizing Statistical Multi-Response Problems Using Genetic Local Search Algorithm Through Fuzzy Goal Programming

M. Amiri, N. Karimi and S.F. Jamshidi

Abstract:
This study presents a methodology for solving multi-response optimization problems. Since goal programming method considers decision maker`s comments objectively, it has special significance; but using this method in large and complex problems alone can`t be, so effective, thus it would be a better idea to use a metaheuristic method. The proposed method is a combination of simulation approach, fuzzy goal programming, genetic algorithm and local search algorithm. This method will use firstly simulation to generate required inputs, secondly fuzzy goal programming to model the problem and finally genetic local search algorithm for problem optimization. At the end we will show the performance of this method by numerical example and designed experiments.
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How to cite this article:

M. Amiri, N. Karimi and S.F. Jamshidi, 2008. A Methodology for Optimizing Statistical Multi-Response Problems Using Genetic Local Search Algorithm Through Fuzzy Goal Programming. Journal of Applied Sciences, 8: 3199-3206.

DOI: 10.3923/jas.2008.3199.3206

URL: https://scialert.net/abstract/?doi=jas.2008.3199.3206

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