Meta-optimization based on self-organizing map and genetic algorithm

Authors:
A. P. Karpenko;Z. O. Svianadze
Affiliations:
Bauman Moscow State Technical University, Moscow, Russian Federation;Bauman Moscow State Technical University, Moscow, Russian Federation
Venue:
Optical Memory and Neural Networks
Year:
2011

Citing 2
Cited 0

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Abstract

The paper considers the parametric optimization of search optimization algorithms (metaoptimization). The meta-optimization method enables to find the best strategy for an algorithm during the execution of the program based on this algorithm. The method uses the clusterization of a set of problems of a particular class with the help of Kohenen self-organizing maps and tackles the metaoptimization problem proper with the aid of the continuous genetic algorithm.