Representations for genetic and evolutionary
algorithms
Spring\-er-Ver\-lag, pub-SV:adr, Second издание, (2006)First published 2002, 2nd edition available
electronically.Аннотация
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 summarises
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 optimisation
methods. Using the developed theory, representations
can be analysed 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.