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Optimizing multi-response statistical problems using a genetic algorithm

Pasandideh, S. H. R ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. Publisher: Sharif University of Technology , 2006
  3. Abstract:
  4. In this paper, two methods to solve multi-response statistical problems are presented. In these methods, desirability function, genetic algorithm and simulation methodology are applied. The desirability function is responsible for modeling the multi-response statistical problem, the genetic algorithm tries to optimize the model and, finally, the simulation approach generates the required input data from a simulated system. The methods differ from each other in controlling the randomness of the problem. In the first method, replications control this randomness, while, in the second method, the randomness is controlled by a statistical test. Furthermore, these methods are compared by designed experiments and the results are reported. © Sharif University of Technology, January 2006
  5. Keywords:
  6. Computer simulation ; Desirability function ; Multi-response statistical problems ; Replications ; Genetic algorithms ; Mathematical models ; Optimization ; Random processes ; Statistical tests ; Genetic algorithm ; Simulation ; Statistical analysis
  7. Source: Scientia Iranica ; Volume 13, Issue 1 , 2006 , Pages 50-59 ; 10263098 (ISSN)
  8. URL: http://scientiairanica.sharif.edu/article_2562.html