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 empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.

Computational Intelligence is a very dynamic domain of modern information society which integrates fields such as neural networks, fuzzy systems, evolutionary computation and intelligent systems in general. The book presents papers from the Euro-International Symposium on Computational Intelligence held in Kosice (Slovak Republic) in August 2000. It contains theoretical studies along with a chapter on applications and case studies. One of the main results of the symposium is that the combination of various techniques into hybrid intelligent systems will be very important for the development of intelligent information systems in the 21st century. The book also contains interesting forewords written by L.A. Zadeh, D.E. Goldberg, and K. Fukushima.