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ID 15386
Eprint ID
15386
FullText URL
Author
Ye Ju
Tanaka, Masahiro
Tanino, Tetsuzo
Abstract
Mutation is one of the important operators in genetic algorithm. In traditional genetic algorithm, mutation is activated stochastically. In this way it is unknown and cannot be controlled for which individuals to be mutated. Therefore, it is unavoidable that some good individuals are destroyed by mutation and then the evolutionary efficiency of the genetic algorithm is dampened. Owing to this kind of destructivity of mutation, the operator of mutation has to be limited within a very small probability, and the potentiality of mutation is consequently limited. In this paper, we present an evolutionary chain-based mutation and a control strategy of reasonable competition, in which the heuristic information provided by the evaluation function is well utilized. This method avoids the blindness of stochastic mutation. The performance improved in this method is shown by two examples, a fuzzy modeling for the identification of a nonlinear function and a typical combinatorial optimization problem-the traveling salesman problem.
Published Date
1995-12-28
Publication Title
Memoirs of the Faculty of Engineering, Okayama University
Publication Title Alternative
岡山大学工学部紀要
Volume
volume30
Issue
issue1
Publisher
Faculty of Engineering, Okayama University
Publisher Alternative
岡山大学工学部
Start Page
111
End Page
120
ISSN
0475-0071
NCID
AA10699856
Content Type
Departmental Bulletin Paper
language
英語
File Version
publisher
Refereed
False
Eprints Journal Name
mfe