Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/70312
Type: Artigo de periódico
Title: Prior detection of genetic algorithm significant parameters: Coupling factorial design technique to genetic algorithm
Author: Costa, CBB
Rivera, EAC
Alves Ferreira Rezende, MC
Maciel, MRW
Filho, RM
Abstract: This work presents an extension of a previous proposed procedure [Costa, C.B.B., Wolf Maciel, M.R., Maciel Filho, R., 2005. Factorial design technique applied to genetic algorithm parameters in a batch cooling crystallization optimization. Computers and Chemical Engineering 29, 2229-2241] to be adopted as a prior analysis in optimization problems to be solved using genetic algorithm (GA). Chemical engineering problems are commonly highly non-linear and possess a large number of variables, sometimes with significant interactions among them. Such characteristics make the optimization problems really difficult to be solved by deterministic methods. GA is an increasing tool for solving this sort of problems. However, no systematic approach to establish the best set of GA parameters for any problem was found in the literature and a relatively easy to use and meaningful approach is proposed and proved to be of general application. The proposed approach consists of applying factorial design, a well-established statistical technique to identify the most meaningful information about the influences of factors on a specific problem, as a support tool to identify the GA parameters with significant effect on the optimization problem. This approach is very useful in conducting further optimization works, since it discharges GA parameters that are not statistically significant for the evolutionary search for the optimum, saving time and computation burden in evolutionary optimization studies. (C) 2007 Elsevier Ltd. All rights reserved.
Subject: factorial design
genetic algorithm
optimization
numerical analysis
parameter identification
computation
Country: Inglaterra
Editor: Pergamon-elsevier Science Ltd
Rights: fechado
Identifier DOI: 10.1016/j.ces.2007.03.042
Date Issue: 2007
Appears in Collections:Unicamp - Artigos e Outros Documentos

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