このエントリーをはてなブックマークに追加
ID 15386
Eprint ID
15386
フルテキストURL
著者
Ye Ju Graduate School of Natural Science and Technology
田中 雅博 Department of Information Technology
谷野 哲三 Department of Information Technology
抄録
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.
発行日
1995-12-28
出版物タイトル
Memoirs of the Faculty of Engineering, Okayama University
出版物タイトル(別表記)
岡山大学工学部紀要
30巻
1号
出版者
Faculty of Engineering, Okayama University
出版者(別表記)
岡山大学工学部
開始ページ
111
終了ページ
120
ISSN
0475-0071
NCID
AA10699856
資料タイプ
紀要論文
言語
English
論文のバージョン
publisher
査読
無し
Eprints Journal Name
mfe