I am very happy to have this opportunity to present the work of Boris
Mirkin, a distinguished Russian scholar in the areas of data analysis
and decision making methodologies. The monograph is devoted entirely to
clustering, a discipline dispersed through many theoretical and
application areas, from mathematical statistics and combina- torial
optimization to biology, sociology and organizational structures. It
compiles an immense amount of research done to date, including many
original Russian de- velopments never presented to the international
community before (for instance, cluster-by-cluster versions of the
K-Means method in Chapter 4 or uniform par- titioning in Chapter 5). The
author's approach, approximation clustering, allows him both to
systematize a great part of the discipline and to develop many in-
novative methods in the framework of optimization problems. The
optimization methods considered are proved to be meaningful in the
contexts of data analysis and clustering. The material presented in this
book is quite interesting and stimulating in paradigms, clustering and
optimization. On the other hand, it has a substantial application
appeal. The book will be useful both to specialists and students in the
fields of data analysis and clustering as well as in biology,
psychology, economics, marketing research, artificial intelligence, and
other scientific disciplines. Panos Pardalos, Series Editor.