Presentation 2011-12-15
A Reproduction Method of Real-Coded Genetic Algorithm Based on Self-Organizing Map
Yoshiaki UEDA, Ryosuke KUBOTA,
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Abstract(in English) Genetic algorithm is a search algorithm based on mechanism of natural selection and natural genetics. To solve optimization problems, a population is updated by using genetic operations (crossover, mutation and reproduction). However, the conventional reproduction method causes a loss of genetic diversity of the population, because the individuals for the next generation are generated by copying those of the present generation. The decrease of genetic diversity leads to ineffectiveness of the search, because the individuals after the reproduction correspond the searching points and the bases of crossover. In this paper, we propose a new reproduction method which uses an idea of a self-organizing map (SOM). To validate the effectiveness of the proposed method, it is applied to four optimization problems of continuous benchmark functions. Furthermore, we also analyze the characteristics of the fitness functions by observing among reference vectors.
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Keyword(in English) Real-coded genetic algorithm / self-organizing map / reproduction / visualization / genetic diversity
Paper # SIS2011-44
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Conference Date 2011/12/8(1days)
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Language JPN
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Title (in English) A Reproduction Method of Real-Coded Genetic Algorithm Based on Self-Organizing Map
Sub Title (in English)
Keyword(1) Real-coded genetic algorithm
Keyword(2) self-organizing map
Keyword(3) reproduction
Keyword(4) visualization
Keyword(5) genetic diversity
1st Author's Name Yoshiaki UEDA
1st Author's Affiliation Department of Intelligent System Engineering, Ube National College of Technology()
2nd Author's Name Ryosuke KUBOTA
2nd Author's Affiliation Department of Intelligent System Engineering, Ube National College of Technology
Date 2011-12-15
Paper # SIS2011-44
Volume (vol) vol.111
Number (no) 342
Page pp.pp.-
#Pages 5
Date of Issue