New Book Announcement

[Kalyanmoy Deb <deb@tik.ee.ethz.ch>]

Please post this announcemnt. Thanks,
Kalyan
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(Apologies if you have received this note more than once)

Title: Multi-Objective Optimization Using Evolutionary Algorithms
Author: KALYANMOY DEB (deb@iitk.ac.in)
Publisher: Chichester, UK: Wiley
Pages: 496 (Hard Cover), 319 figures
ISBN: 0471 87339 X
http://catalog.wiley.com/remtitle.cgi?isbn=047187339X&country=826

The above book is now available from John Wiley & Sons, UK.
One of the niches of evolutionary
algorithms in solving search and optimization problems
is the elegance and efficiency in which they can solve
multi-objective optimization problems. Multi-objective optimization
deals with multiple and often conflicting objectives, thereby
resulting in a set of optimal solutions instead of a single optimal
solution. This book is the first comprehensive book introducing
multi-objective optimization, classical multi-objective optimization
methods, evolutionary algorithms, and immediate research topics in the
emerging field of multi-objective evolutionary algorithms.

The highlights of the book:
o Comprehensive coverage of the growing area of multi-objective evolutionary
  algorithms
o Carefully introduces each algorithm with examples and in-depth discussion
o Includes a number of real-world problems from engineering and sciences
o Includes discussion of advanced topics and future research
o Includes an extensive reference list of current research studies
o Accessible to those with limited knowledge of classical multi-objective
  optimization and evolutionary algorithms

The integrated presentation of theory, algorithms and examples will
benefit those working and researching in the areas of optimization, optimal
design and evolutionary computing. This text provides an excellent
introduction to the use of evolutionary algorithms in multi-objective
optimization, allowing use as a graduate course text or for self-study.

Multi-Objective Optimization Using Evolutionary Algorithms
by Kalyanmoy Deb
CONTENTS:
Foreword by David E. Goldberg
Preface
Prologue
Multi-Objective Optimization
Classical Methods
Evolutionary Algorithms
Non-elitist multi-objective evolutionary algorithms
Elitist multi-objective evolutionary algorithms
Constrained multi-objective evolutionary algorithms
Salient Issues of multi-objective evolutionary algorithms
Applications of multi-objective evolutionary algorithms
Epilogue
References
Index
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