Linkage in Evolutionary Computation

Author:   Ying-ping Chen ,  Meng-Hiot Lim
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Edition:   2008 ed.
Volume:   157
ISBN:  

9783540850670


Pages:   488
Publication Date:   26 September 2008
Format:   Hardback
Availability:   In Print   Availability explained
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Linkage in Evolutionary Computation


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Overview

In recent years, the issue of linkage in GEAs has garnered greater attention and recognition from researchers. Conventional approaches that rely much on ad hoc tweaking of parameters to control the search by balancing the level of exploitation and exploration are grossly inadequate. As shown in the work reported here, such parameters tweaking based approaches have their limits; they can be easily ”fooled” by cases of triviality or peculiarity of the class of problems that the algorithms are designed to handle. Furthermore, these approaches are usually blind to the interactions between the decision variables, thereby disrupting the partial solutions that are being built up along the way.

Full Product Details

Author:   Ying-ping Chen ,  Meng-Hiot Lim
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2008 ed.
Volume:   157
Dimensions:   Width: 15.50cm , Height: 2.60cm , Length: 23.50cm
Weight:   0.910kg
ISBN:  

9783540850670


ISBN 10:   3540850678
Pages:   488
Publication Date:   26 September 2008
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Models and Theories.- Parallel Bivariate Marginal Distribution Algorithm with Probability Model Migration.- Linkages Detection in Histogram-Based Estimation of Distribution Algorithm.- Linkage in Island Models.- Real-Coded ECGA for Solving Decomposable Real-Valued Optimization Problems.- Linkage Learning Accuracy in the Bayesian Optimization Algorithm.- The Impact of Exact Probabilistic Learning Algorithms in EDAs Based on Bayesian Networks.- Linkage Learning in Estimation of Distribution Algorithms.- Operators and Frameworks.- Parallel GEAs with Linkage Analysis over Grid.- Identification and Exploitation of Linkage by Means of Alternative Splicing.- A Clustering-Based Approach for Linkage Learning Applied to Multimodal Optimization.- Studying the Effects of Dual Coding on the Adaptation of Representation for Linkage in Evolutionary Algorithms.- Symbiotic Evolution to Avoid Linkage Problem.- EpiSwarm, a Swarm-Based System for Investigating Genetic Epistasis.- Real-Coded Extended Compact Genetic Algorithm Based on Mixtures of Models.- Applications.- Genetic Algorithms for the Airport Gate Assignment: Linkage, Representation and Uniform Crossover.- A Decomposed Approach for the Minimum Interference Frequency Assignment.- Set Representation and Multi-parent Learning within an Evolutionary Algorithm for Optimal Design of Trusses.- A Network Design Problem by a GA with Linkage Identification and Recombination for Overlapping Building Blocks.- Knowledge-Based Evolutionary Linkage in MEMS Design Synthesis.

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