# 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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