Evolution strategies for objective functions with locally correlated variables

Authors:
Piotr Lipinski
Affiliations:
Institute of Computer Science, University of Wroclaw, Wroclaw, Poland
Venue:
IDEAL'10 Proceedings of the 11th international conference on Intelligent data engineering and automated learning
Year:
2010

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Cited 0

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Abstract

This paper proposes an improvement of Evolutionary Strategies for objective functions with locally correlated variables. It focusses on detecting local dependencies among variables of the objective function on the basis of the current population and transforming the original objective function into a new one of a smaller number of variables. Such a transformation is updated in successive iterations of the evolutionary algorithm to reflect local dependencies over successive neighborhoods of optimal solutions. Experiments performed on some popular benchmark functions confirm that the improved algorithm outperforms the original one.