DocumentCode
1449442
Title
Fitness sharing and niching methods revisited
Author
Sareni, Bruno ; Krähenbühl, Laurent
Author_Institution
CEGELY, UPRESA CNRS, Ecully, France
Volume
2
Issue
3
fYear
1998
fDate
9/1/1998 12:00:00 AM
Firstpage
97
Lastpage
106
Abstract
Interest in multimodal optimization function is expanding rapidly since real-world optimization problems often require the location of multiple optima in the search space. In this context, fitness sharing has been used widely to maintain population diversity and permit the investigation of manly peaks in the feasible domain. This paper reviews various strategies of sharing and proposes new recombination schemes to improve its efficiency. Some empirical results are presented for high and a limited number of fitness function evaluations. Finally, the study compares the sharing method with other niching techniques
Keywords
genetic algorithms; evolutionary computation; fitness sharing; genetic algorithms; multimodal optimization; niching methods; Animals; Ecosystems; Evolutionary computation; Genetic algorithms; Optimization methods; Shape; Standards development; Testing;
fLanguage
English
Journal_Title
Evolutionary Computation, IEEE Transactions on
Publisher
ieee
ISSN
1089-778X
Type
jour
DOI
10.1109/4235.735432
Filename
735432
Link To Document