Estimation of distribution algorithms with mutation

Authors:
Hisashi Handa
Affiliations:
Okayama University, Okayama, Japan
Venue:
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2005

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Abstract

The Estimation of Distribution Algorithms are a class of evolutionary algorithms which adopt probabilistic models to reproduce the genetic information of the next generation, instead of conventional crossover and mutation operations. In this paper, we propose new EDAs which incorporate mutation operator to conventional EDAs in order to keep the diversities in EDA populations. Empirical experiments carried out this paper confirm us the effectiveness of the proposed methods.