Felix Streichert, Gunnar Stein, Holger Ulmer, and Andreas Zell

A Clustering Based Niching EA for Multimodal Search Spaces

Proceedings of the 6th International Conference on Artificial Evolution

Abstract

We propose a new niching method for Evolutionary Algorithms which is able to identify and track global and local optima in a multimodal search space. To prevent the loss of diversity we replace the global selection pressure within a single population by local selection of a multi-population strategy. The sub-populations representing species specialized on niches are dynamically identified using standard clustering algorithms on a primordial population. With this multi-population strategy we are able to preserve diversity within the population and to identify global/local optima directly without further post-processing.

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BibTeX 

@InProceedings{streichert03clustering,
  author 		= "Felix Streichert and Gunnar Stein and Holger Ulmer and Andreas Zell",
  title 		= "A Clustering Based Niching EA for Multimodal Search Spaces ",
  booktitle 		= "Proceedings of the 6th International Conference on Artificial Evolution",
  editor 		= "",
  year 			= "2003",
  pages 		= "",
  address 		= "Marseille, France ",
  publisher 		= {Springer Verlag},
  publisher_address 	= {Berlin}, 
  month	 		= "27-30 October",
  volume 		= "",
  series 		= "",
  ISBN 			= {},
  url 			= "http://www.ra.cs.uni-tuebingen.de/mitarb/streiche/publication/streichert03clustering.html" 
}