Large Accelerating a GA Convergence by Fitting a Single-Peak Function
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- TAKAGI Hideyuki
- Dept. of Art and Information Desigh Kyushu Institute of Desigh
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- INGU Takeo
- Deloitte Touche Tohmatsu
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- OHNISHI Kei
- Graduate School, kyushu Institute of Desigh
Bibliographic Information
- Other Title
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- 単峰性関数当てはめによるGA収束高速化
- タンホウセイ カンスウ アテハメ ニ ヨル GA シュウソク コウソクカ
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Abstract
This paper proposes an acceleration method of GA search that finds a new elite by fitting a single-peak function on fitness landscape. The roughest approximation of a finite fitness landscape that has one global optimum would be a single-peak curved surface, and the vertex of the approximated single-peak function is expected to be near the global optimum of the original searching space. We propose two data selection methods for the fitting, use a quadratic function as the single-peak function, and evaluate the proposed idea using seven benchmark functions. The experimental results have shown that the proposed method accelerate GA convergence.
Journal
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- Journal of Japan Society for Fuzzy Theory and Intelligent Informatics
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Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 15 (2), 219-229, 2003
Japan Society for Fuzzy Theory and Intelligent Informatics