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| Titel: |
A Methodology for Optimizing Statistical Multi-Response Problems Using Genetic Local Search Algorithm Through Fuzzy Goal Programming |
| Auteur: |
M. Amiri N. Karimi S.F. Jamshidi |
| Verschenen in: |
Journal of applied sciences |
| Paginering: | Jaargang 8 (2008) nr. 18 pagina's 3199-3206 |
| Jaar: |
2008 |
| Inhoud: |
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. |
| Uitgever: |
Asian Network for Scientific Information (provided by DOAJ) |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 11 van 160 gevonden artikelen
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