| ID | 30054 |
| フルテキストURL | |
| 著者 |
Katai, Osamu
Kyoto University
Konishi, Tadataka
Okayama University
Baba, Mitsuru
Okayama University
|
| 抄録 | In this paper, we discuss how many satisfiable solutions a genetic algorithm can find in a problem instance of a constraint satisfaction problems in a single execution. Hence, we propose a framework for a new fitness function which can be applied to traditional fitness functions. However, the mechanism of the proposed fitness function is quite simple, and several experimental results on a variety of instances of general constraint satisfaction problems demonstrate the effectiveness of the proposed fitness function |
| キーワード | constraint theory
functions
genetic algorithms
operations research
|
| 備考 | Digital Object Identifier: 10.1109/CEC.2000.870783
Published with permission from the copyright holder. This is the institute's copy, as published in Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 16-19 July 2000, Vol. 2, Pages 1184-1189. Publisher URL:http://dx.doi.org/10.1109/CEC.2000.870783 Copyright © 2000 IEEE. All rights reserved. |
| 発行日 | 2000-7
|
| 出版物タイトル |
Evolutionary Computation
|
| 巻 | 2巻
|
| 開始ページ | 1184
|
| 終了ページ | 1189
|
| 資料タイプ |
学術雑誌論文
|
| 言語 |
英語
|
| 査読 |
有り
|
| DOI | |
| Submission Path | industrial_engineering/41
|
