Representations for Genetic and Evolutionary Algorithms
Editorial Reviews
Book Description
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.
Book Info
This monograph breaks with the 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.
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Representations for Genetic and Evolutionary Algorithms,Franz Rothlauf,Springer,354025059X,Applied,Artificial Intelligence - General,Group Theory,Mathematics,Operations Research,Science/Mathematics,GEA,Genetic and Evolutionary Algorithms,Integer Representations,Mathematics / Applied,Optimal Communication Spanning Tree Problems,Theory of Representation,Tree Representations
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