Authors:
- A theory of representations is not taken as given, but is developed and applied to real-world problems of commercial importance
- Considers basic concepts of representations, such as redundancy, scaling and locality
- Completely overhauled 2nd edition of this easily readable and successful book
Buy it now
Buying options
Tax calculation will be finalised at checkout
Other ways to access
This is a preview of subscription content, log in via an institution to check for access.
Table of contents (9 chapters)
-
Front Matter
-
Back Matter
About this book
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.
Authors and Affiliations
-
School of Business Administration, Universität Mannheim, Mannheim, Germany
Franz Rothlauf
Bibliographic Information
Book Title: Representations for Genetic and Evolutionary Algorithms
Authors: Franz Rothlauf
DOI: https://doi.org/10.1007/3-540-32444-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-25059-3Published: 10 January 2006
Softcover ISBN: 978-3-642-06410-4Published: 14 October 2010
eBook ISBN: 978-3-540-32444-7Published: 14 March 2006
Edition Number: 2
Number of Pages: XVII, 325
Additional Information: Originally published as volume 104 in the series "Studies in Fuzziness and Soft Computing"
Topics: Mathematical and Computational Engineering, Artificial Intelligence, Operations Research/Decision Theory, IT in Business