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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.
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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.
The whole volume consisting of 19 chapters is divided into 3 parts: Models and Theories; Operators and Frameworks; Applications. This edited volume will serve as a useful guide and reference for researchers who are currently working in the area of linkage. For postgraduate research students, this volume will serve as a good source of reference. It is also suitable as a text for a graduate level course focusing on linkage issues. For practitioners who are looking at putting into practice the concept of linkage, the few chapters on applications will serve as a useful guide.
Title: LINKAGE IN EVOLUTIONARY COMPUTATION
Publisher: Springer
Publication Date: 2008
Binding: Hardcover
Condition: Brand New
Seller: Buchpark, Trebbin, Germany
Condition: Sehr gut. Zustand: Sehr gut | Seiten: 500 | Sprache: Englisch | Produktart: Bücher | 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. Seller Inventory # 4562315/12
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Seller: Basi6 International, Irving, TX, U.S.A.
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service. Seller Inventory # ABEOCT25-244732
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Buch. Condition: Neu. Linkage in Evolutionary Computation | Ying-Ping Chen | Buch | Studies in Computational Intelligence | xii | Englisch | 2008 | Springer | EAN 9783540850670 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 101770863