| ID | 30054 |
| FullText URL | |
| Author |
Katai, Osamu
Konishi, Tadataka
Baba, Mitsuru
|
| Abstract | 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 |
| Keywords | constraint theory
functions
genetic algorithms
operations research
|
| Note | 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. |
| Published Date | 2000-7
|
| Publication Title |
Evolutionary Computation
|
| Volume | volume2
|
| Start Page | 1184
|
| End Page | 1189
|
| Content Type |
Journal Article
|
| language |
English
|
| Refereed |
True
|
| DOI | |
| Submission Path | industrial_engineering/41
|
