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A Study of Parameter Optimization in Meta-Genetic Algorithm 白滝, 順 Shirataki, Jun 富川, 武彦 Tomikawa, Takehiko Genetic Algorithm Meta-GA Parameter Optimization application/pdf Genetic Algorithm is governed by its system parameters which are usually set in a heuristic manner at present. These parameters; the reproduction rate, the crossover rate, the mutation rate, and the population size are set to appropriate values depending on the characteristics of the target problem. This paper studies the behavior of the Meta-GA system which searches for the best parameter values for the problem oriented task-GA. Here the "number of generation cycles" is utilized to evaluate the performance of the task-GA. The experimental simulation was carried out to solve the standard functions of DeJong while the parameters of meta-GA are fixed. 神奈川工科大学 2000-03-20 eng departmental bulletin paper VoR https://doi.org/10.34411/00000883 http://hdl.handle.net/10368/883 https://kait.repo.nii.ac.jp/records/890 10.34411/00000883 AN10074179 09161902 神奈川工科大学研究報告.B,理工学編 24 63 66 https://kait.repo.nii.ac.jp/record/890/files/kkb-024-010.pdf application/pdf 1.7 MB 2010-02-03