Representations for Genetic and Evolutionary Algorithms is written by the author.

Many theory and empirical study have been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph 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 basic concepts of representations, such as redundancy, scaling and locality, are considered in the book. Theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts can be used to solve network design problems. The results show that proper representations are important.

FROM THE BACK COVER

Operators and test problems have been the focus of a large amount of theory and empirical study in the field of GEAs. This book gives a comprehensive overview of the influence of problem representations on GEA performance. It’s not like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it The book describes the basic properties of representations and how they affect the performance of GEAs. Representations can be analyzed and designed using a theory. Network design problems can be solved using the theoretical concepts. It’s not like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it The book is written in an easy-to-read style and is intended for researchers, practitioners, and students who want to learn about representations. A new chapter on the analysis of direct representations is included in the second edition.