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Published in:
2011 | OriginalPaper | Chapter
Global Optimization with the Gaussian Polytree EDA
Authors : Ignacio Segovia Domínguez, Arturo Hernández Aguirre, Enrique Villa Diharce
Published in: Advances in Soft Computing
Publisher: Springer Berlin Heidelberg
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This paper introduces the Gaussian polytree estimation of distribution algorithm, a new construction method, and its application to estimation of distribution algorithms in continuous variables. The variables are assumed to be Gaussian. The construction of the tree and the edges orientation algorithm are based on information theoretic concepts such as mutual information and conditional mutual information. The proposed Gaussian polytree estimation of distribution algorithm is applied to a set of benchmark functions. The experimental results show that the approach is robust, comparisons are provided.