In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily "fooled" by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.
| ISBN: | 9783540850670 |
| Publication date: | 26th September 2008 |
| Author: | Yingping Chen, MengHiot Lim |
| Publisher: | Springer an imprint of Springer Berlin Heidelberg |
| Format: | Hardback |
| Pagination: | 486 pages |
| Series: | Studies in Computational Intelligence |
| Genres: |
Computer-aided design (CAD) Artificial intelligence Maths for engineers |
In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate.
Linkage in Evolutionary Computation features in the following genres: Computer-aided design (CAD), Artificial intelligence, Maths for engineers
Hardback. Not Available.
Linkage in Evolutionary Computation was written by Yingping Chen, MengHiot Lim and published by Springer an imprint of Springer Berlin Heidelberg
Linkage in Evolutionary Computation has 486 pages
Yes it is part of Studies in Computational Intelligence series