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 Japanese) | (See Japanese page) |
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. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | genetic algorithms / local search / global search / elitism strategy / hybrid |
Paper # | NC2004-102 |
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Committee | NC |
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Conference Date | 2004/11/20(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Neurocomputing (NC) |
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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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