Representations for Genetic and Evolutionary Algorithms

Representations for Genetic and Evolutionary Algorithms

Franz Rothlauf

244,34 €
IVA incluido
Disponible
Editorial:
Springer Nature B.V.
Año de edición:
2010
ISBN:
9783642064104
244,34 €
IVA incluido
Disponible

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Sobre IBD

In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. The book summarizes existing knowledge regarding problem representations and describes how basic properties of representations, such as redundancy, scaling, or locality, influence the performance of GEAs and other heuristic optimization methods. Using the developed theory, representations can be analyzed and designed in a theory-guided matter. The theoretical concepts are used for solving integer optimization problems and network design problems more efficiently. The book is written in an easy-readable style and is intended for researchers, practitioners, and students who want to learn about representations. This second edition extends the analysis of the basic properties of representations and introduces a new chapter on the analysis of direct representations.

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Otros libros del autor

  • Representations for Genetic and Evolutionary Algorithms
    Franz Rothlauf
    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 empir...
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  • Representations for Genetic and Evolutionary Algorithms
    Franz Rothlauf
    In the field of genetic and evolutionary algorithms (GEAs), a large amount of theory and empirical study has been focused on operators and test problems, while problem representation has often been taken as given. This book breaks with this tradition and provides a comprehensive overview on the influence of problem representations on GEA performance. ...