Presentation 2004/11/20
A Study on Hybrid Binary-Coded Genetic Algorithm with Local Search
Hong ZHANG, Masumi ISHIKAWA,
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Abstract(in English) In this paper we propose a hybrid binary-coded genetic algorithm with local search for the performance improvement of the solution search in optimization problems. The key idea of this proposal is that the local search that has the efficiency, the non-redundant search that maintains diversity and the elitism strategy that improves convergence for the solution search are carried out simultaneously. Consequently, it is able to expect to efficiently rearch an approximation solution by exericising the merits both of global search and local search. To evaluate the effectiveness of the proposed method, computer experiments such as combinatorial optimization problem and pattern classification problem are implemented. The obtained results are shown to discover the optimal solution with search of a few generations.
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Keyword(in English) genetic algorithms / local search / global search / elitism strategy / hybrid
Paper # NC2004-102
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Committee NC
Conference Date 2004/11/20(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Study on Hybrid Binary-Coded Genetic Algorithm with Local Search
Sub Title (in English)
Keyword(1) genetic algorithms
Keyword(2) local search
Keyword(3) global search
Keyword(4) elitism strategy
Keyword(5) hybrid
1st Author's Name Hong ZHANG
1st Author's Affiliation Graduate School of Life Science & Systems Engineering Kyushu Institute of Technology()
2nd Author's Name Masumi ISHIKAWA
2nd Author's Affiliation Graduate School of Life Science & Systems Engineering Kyushu Institute of Technology
Date 2004/11/20
Paper # NC2004-102
Volume (vol) vol.104
Number (no) 474
Page pp.pp.-
#Pages 6
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