Overview
- Presents recent results in Linkage in Evolutionary Computation
Part of the book series: Studies in Computational Intelligence (SCI, volume 157)
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Table of contents (19 chapters)
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Models and Theories
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Operators and Frameworks
Keywords
About this book
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.
Bibliographic Information
Book Title: Linkage in Evolutionary Computation
Editors: Ying-ping Chen, Meng-Hiot Lim
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-85068-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-85067-0Published: 26 September 2008
Softcover ISBN: 978-3-642-09876-5Published: 28 October 2010
eBook ISBN: 978-3-540-85068-7Published: 10 September 2008
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XII, 488
Number of Illustrations: 227 b/w illustrations
Topics: Computer-Aided Engineering (CAD, CAE) and Design, Mathematical and Computational Engineering, Artificial Intelligence