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A review on Estimation of Distribution Algorithms in Permutation-based Combinatorial Optimization Problems
(2011)
Estimation of Distribution Algorithms (EDAs) are a set of algorithms
that belong to the field of Evolutionary Computation. Characterized by the use of
probabilistic models to represent the solutions and the dependencies ...
New methods for generating populations in Markov network based EDAs: Decimation strategies and model-based template recombination
(2012-12-27)
Methods for generating a new population are a fundamental component of estimation of distribution algorithms (EDAs). They serve to transfer the information contained in the probabilistic model to the new generated population. ...
Analyzing limits of effectiveness in different implementations of estimation of distribution algorithms
(2011)
Conducting research in order to know the range of problems in which a search
algorithm is effective constitutes a fundamental issue to understand the algorithm
and to continue the development of new techniques. In this ...
MATEDA: A suite of EDA programs in Matlab
(2009)
This paper describes MATEDA-2.0, a suite of programs in Matlab for
estimation of distribution algorithms. The package allows the optimization of single and multi-objective problems with estimation of distribution
algorithms ...
A quantitative analysis of estimation of distribution algorithms based on Bayesian networks
(2009)
The successful application of estimation of distribution algorithms
(EDAs) to solve different kinds of problems has reinforced their candidature
as promising black-box optimization tools. However, their internal behavior
is ...
On the application of estimation of distribution algorithms to multi-marker tagging SNP selection
(2009)
This paper presents an algorithm for the automatic selection of a
minimal subset of tagging single nucleotide polymorphisms (SNPs) using an estimation of distribution algorithm (EDA). The EDA stochastically searches the ...
Using network mesures to test evolved NK-landscapes
(2012)
In this paper we empirically investigate which are the structural characteristics that can help to predict the complexity of NK-landscape instances for estimation of distribution algorithms. To this end, we evolve instances ...
Extending Distance-based Ranking Models In Estimation of Distribution Algorithms
(2014-05-20)
Recently, probability models on rankings have been proposed in the field of estimation of distribution algorithms in order to solve permutation-based combinatorial optimisation problems. Particularly, distance-based ranking ...
The Linear Ordering Problem Revisited
(2014-01-08)
The Linear Ordering Problem is a popular combinatorial optimisation problem which has been extensively addressed in the literature. However, in spite of its popularity, little is known about the characteristics of this ...