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 :
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