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Mateda-2.0: Estimation of Distribution Algorithms in MATLAB

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Date
2010-07
Author
Santana Hermida, Roberto
Bielza, Concha
Larrañaga, Pedro
Lozano Alonso, José Antonio
Echegoyen, Carlos
Mendiburu Alberro, Alexander
Armañanzas Arnedillo, Rubén
Shakya, Siddartha
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Journal of Statistical Software 35(7) : 1-30 (2010)
URI
http://hdl.handle.net/10810/11887
Abstract
This paper describes Mateda-2.0, a MATLAB package for estimation of distribution algorithms (EDAs). This package can be used to solve single and multi-objective discrete and continuous optimization problems using EDAs based on undirected and directed probabilistic graphical models. The implementation contains several methods commonly employed by EDAs. It is also conceived as an open package to allow users to incorporate different combinations of selection, learning, sampling, and local search procedures. Additionally, it includes methods to extract, process and visualize the structures learned by the probabilistic models. This way, it can unveil previously unknown information about the optimization problem domain. Mateda-2.0 also incorporates a module for creating and validating function models based on the probabilistic models learned by EDAs.
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