Presentation | 1999/3/4 An Execution Model of Genetic Algorithms and a Supporting Environment : multiple individual sets and best individuals Yoshiharu Muramatsu, Yoshihisa Mano, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Genetic algorithms(GAs), an optimization technique by simulating the process of natural evolution, have been successfully applied to many optimization problelms which are difficult to solve exactly by conventional methods. However GAs have several weaknesses in terms of the ability to handle local search. And another thing is that many its individuals will get into local solutions. An execution model of GAs is described, which provides more powerful local search and keeps the diversity of individuals. In this model a set of individuals evolves forwards one of solutions and the neighborhood near the best individuals. In the set is searched. This model is suited to parallel execution. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | genetic algorithm / local search / diversity of individuals / parallel execution |
Paper # | AI98-77 |
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Committee | AI |
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Conference Date | 1999/3/4(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | An Execution Model of Genetic Algorithms and a Supporting Environment : multiple individual sets and best individuals |
Sub Title (in English) | |
Keyword(1) | genetic algorithm |
Keyword(2) | local search |
Keyword(3) | diversity of individuals |
Keyword(4) | parallel execution |
1st Author's Name | Yoshiharu Muramatsu |
1st Author's Affiliation | Department of Business Administration,Graduate School of Nanzan University() |
2nd Author's Name | Yoshihisa Mano |
2nd Author's Affiliation | Department of Business Administration,Graduate School of Nanzan University |
Date | 1999/3/4 |
Paper # | AI98-77 |
Volume (vol) | vol.98 |
Number (no) | 634 |
Page | pp.pp.- |
#Pages | 6 |
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