Representations for Genetic and Evolutionary Algorithms /

In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of r...

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Bibliographic Details
Main Author: Rothlauf, Franz
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Heidelberg : Physica-Verlag HD, 2002.
Series:Studies in fuzziness and soft computing ; 104.
Subjects:
Online Access:Connect to the full text of this electronic book
Description
Summary:In the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.
Item Description:Electronic resource.
Physical Description:1 online resource (xiv, 289 pages 99 illustrations)
ISBN:9783642880940 (electronic bk.)
3642880940 (electronic bk.)
ISSN:1434-9922 ;