Critical Issues in Model-Based Surrogate Functions in Estimation of Distribution Algorithms

作者: Roberto Santana , Alexander Mendiburu , Jose A. Lozano

DOI: 10.1007/978-3-319-03756-1_1

关键词:

摘要: In many optimization domains the solution of the problem can be made more efficient by the construction of a surrogate fitness model. Estimation of distribution algorithms (EDAs) are a …

参考文章(49)
Hossein Karshenas, Roberto Santana, Concha Bielza, Pedro Larrañaga, Continuous Estimation of Distribution Algorithms Based on Factorized Gaussian Markov Networks Springer, Berlin, Heidelberg. pp. 157- 173 ,(2012) , 10.1007/978-3-642-28900-2_10
Carlos A. Coello Coello, Gary B. Lamont, David A. Van Veldhuizen, Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation) Springer-Verlag New York, Inc.. ,(2006)
Iñaki Inza, Endika Bengoetxea, Jose A. Lozano, Pedro Larrañaga, Towards a New Evolutionary Computation: Advances on Estimation of Distribution Algorithms (Studies in Fuzziness and Soft Computing) Springer-Verlag New York, Inc.. ,(2006)
Carlos Echegoyen, Alexander Mendiburu, Roberto Santana, Jose A. Lozano, Analyzing the k Most Probable Solutions in EDAs Based on Bayesian Networks Springer, Berlin, Heidelberg. pp. 163- 189 ,(2010) , 10.1007/978-3-642-12834-9_8
Alexander E. I. Brownlee, John A. W. McCall, Siddhartha K. Shakya, The Markov Network Fitness Model Springer, Berlin, Heidelberg. pp. 125- 140 ,(2012) , 10.1007/978-3-642-28900-2_8
Siddhartha Shakya, Roberto Santana, Markov Networks in Evolutionary Computation Springer Publishing Company, Incorporated. ,(2012) , 10.1007/978-3-642-28900-2
Peter R. de Waal, Linda C. van der Gaag, Inference and Learning in Multi-dimensional Bayesian Network Classifiers european conference on symbolic and quantitative approaches to reasoning and uncertainty. pp. 501- 511 ,(2007) , 10.1007/978-3-540-75256-1_45