The mixture of trees factorized distribution algorithm

“The mixture of trees factorized distribution algorithm” by R. Santana, A. Ochoa, and M. R. Soto, Institute of Cybernetics. Mathematics and Physics technical report ICIMAF 2000-129, (Havana, Cuba), Jan. 2001.

Abstract

This paper introduces the Mixtures of Trees Factorized Distribution Algorithm (MT-FDA). It is based on a mixture of trees distribution and the Estimation Maximization learning algorithm. The probabilistic model and the learning procedure of the MT-FDA differ to previous proposals of probabilistic modeling in the context of Evolutionary Computation. Preliminary results show that the MT-FDA overperforms Factorized Distribution Algorithms that use up to second order statistics. It is also competitive, and some times superior to Bayesian Factorized Distribution Algorithms. The paper illustrates how the MT-FDA can incorporate information about particular features of the search space by conveniently selecting the mixture of trees parameters.

BibTeX entry:

@techreport{Santana_et_al:2001,
   author = {R. Santana and A. Ochoa and M. R. Soto},
   title = {The mixture of trees factorized distribution algorithm},
   institution = {Institute of Cybernetics, Mathematics and Physics},
   number = {ICIMAF 2000-129},
   address = {Havana, Cuba},
   month = jan,
   year = {2001},
   issn = {0138-8916}
}

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