Parallel genetic algorithm with adaptive genetic parameters tuned by fuzzy reasoning

概要

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Genetic algorithms (GAs) have several problems, the important of which isthat the search ability of ordinary GAs is not always optimal in the early and final stagesof the search because of fixed GA parameters. Therefore, we have already proposed thefuzzy adaptive search method for genetic algorithms which is able to tune the geneticparameters according to the search stage by the fuzzy rule.In this paper, a fuzzy adaptive search method for parallel genetic algorithms is proposed,in which the high-speed search ability of fuzzy adaptive tuning by FASGA is combinedwith and the high-quality solution capacity of parallel genetic algorithms. The proposedmethod offers improved search performance, and produces high-quality solutions.Simulations are performed to confirm the efficiency of the proposed method, which isshown to be superior to both ordinary and parallel genetic algorithms.
ICIC Internationalの論文
2005-03-00