Jose A. Lozano / Pedro Larrañaga / Iñaki Inza / Endika Bengoetxea (eds.)

Towards a New Evolutionary Computation

Advances on Estimation of Distribution Algorithms
Herausgegeben:Lozano, Jose A.; Larrañaga, Pedro; Inza, Iñaki; Bengoetxea, Endika

• Gebundenes Buch

Produktbeschreibung

Estimation of Distribution Algorithms (EDAs) are a set of algorithms in the Evolutionary Computation (EC) field characterized by the use of explicit probability distributions in optimization. Contrarily to other EC techniques such as the broadly known Genetic Algorithms (GAs) in EDAs, the crossover and mutation operators are substituted by the sampling of a distribution previously learnt from the selected individuals. EDAs have experienced a high development that has transformed them into an established discipline within the EC field.

This book attracts the interest of new researchers in the EC field as well as in other optimization disciplines, and that it becomes a reference for all of us working on this topic. The twelve chapters of this book can be divided into those that endeavor to set a sound theoretical basis for EDAs, those that broaden the methodology of EDAs and finally those that have an applied objective.

Produktdetails

• Studies in Fuzziness and Soft Computing 192
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 11007937, 978-3-540-29006-3
• 2006
• Seitenzahl: 312
• Erscheinungstermin: 12. Januar 2006
• Englisch
• Abmessung: 241mm x 160mm x 22mm
• Gewicht: 562g
• ISBN-13: 9783540290063
• ISBN-10: 3540290060
• Artikelnr.: 15027132

Autorenporträt

Jose A. Lozano, University of the Basque Country, San Sebastian, Spain / Pedro Larranaga, University of the Basque Country, San Sebastian, Spain / Iñaki Inza, University of the Basque Country, San Sebastian, Spain / Endika Bengotxea, University of the Basque Country, San Sebastian, Spain

Inhaltsangabe

Linking Entropy to Estimation of Distribution Algorithms.- Entropy-based Convergence Measurement in Discrete Estimation of Distribution Algorithms.- Real-coded Bayesian Optimization Algorithm.- The CMA Evolution Strategy: A Comparing Review.- Estimation of Distribution Programming: EDA-based Approach to Program Generation.- Multi-objective Optimization with the Naive ID A.- A Parallel Island Model for Estimation of Distribution Algorithms.- GA-EDA: A New Hybrid Cooperative Search Evolutionary Algorithm.- Bayesian Classifiers in Optimization: An EDA-like Approach.- Feature Ranking Using an EDA-based Wrapper Approach.- Learning Linguistic Fuzzy Rules by Using Estimation of Distribution Algorithms as the Search Engine in the COR Methodology.- Estimation of Distribution Algorithm with 2-opt Local Search for the Quadratic Assignment Problem.