Presentation 1999/5/28
A Parallel Genetic Algorithm with Distributed Environment Schema
M. Miki, T. Hiroyasu, M. Kaneko, K. Hatanaka,
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Abstract(in English) This paper introduces an alternative approach to relieving the task of choosing optimal mutation and crossover rates by using a parallel and distributed GA with distributed environments. It is shown that the best mutation and crossover rates depend on the population sizes and the problems, and those are different between a single and multiple populations. The proposed distributed environment GA uses various combination of the parameters as the fixed values in the subpopulations. The excellent performance of the new schema is experimentally recognized for two different types of optimization problems. It is concluded that the distributed environment GA is the fastest /ay to gain the best solution under the given population size and uncertainty of the appropriate crossover and mutation rates.
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Keyword(in English) Optimization / Evolutionary strategy / Genetic Algorithms / Distributed Populations / Parallel Processing / Distributed Environment
Paper # AI99-21
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Committee AI
Conference Date 1999/5/28(1days)
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Registration To Artificial Intelligence and Knowledge-Based Processing (AI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Parallel Genetic Algorithm with Distributed Environment Schema
Sub Title (in English)
Keyword(1) Optimization
Keyword(2) Evolutionary strategy
Keyword(3) Genetic Algorithms
Keyword(4) Distributed Populations
Keyword(5) Parallel Processing
Keyword(6) Distributed Environment
1st Author's Name M. Miki
1st Author's Affiliation Department of Knowledge Engineering, Doshisha University()
2nd Author's Name T. Hiroyasu
2nd Author's Affiliation Department of Knowledge Engineering, Doshisha University
3rd Author's Name M. Kaneko
3rd Author's Affiliation Graduate School of Engineering, Doshisha University
4th Author's Name K. Hatanaka
4th Author's Affiliation Graduate School of Engineering, Doshisha University
Date 1999/5/28
Paper # AI99-21
Volume (vol) vol.99
Number (no) 96
Page pp.pp.-
#Pages 8
Date of Issue