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Genetic and Evolutionary Computation

Evolutionary Algorithms for Solving Multi-Objective Problems

Authors: Coello Coello, Carlos, Lamont, Gary B., van Veldhuizen, David A.

  • Designed for courses on Evolutionary Multi-objective Optimization and Evolutionary Algorithms
  • 2nd Edition is completely updated and presents the latest research
  • Provides a complete set of teaching tutorials, exercises and solutions
  • Contains exhaustive appendices, index and bibliography
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eBook $89.00
price for USA (gross)
  • ISBN 978-0-387-36797-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $124.00
price for USA
  • ISBN 978-0-387-33254-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $124.00
price for USA
  • ISBN 978-1-4899-9460-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

This textbook is the second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly augmented with contemporary knowledge and adapted for the classroom. All the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and student-friendly fashion, incorporating state-of-the-art research results. The diversity of serial and parallel MOEA structures are given, evaluated and compared. The book provides detailed insight into the application of MOEA techniques to an array of practical problems. The assortment of test suites are discussed along with the variety of appropriate metrics and relevant statistical performance techniques.

Distinctive features of the new edition include:

  • Designed for graduate courses on Evolutionary Multi-Objective Optimization, with exercises and links to a complete set of teaching material including tutorials

  • Updated and expanded MOEA exercises, discussion questions and research ideas at the end of each chapter

  • New chapter devoted to coevolutionary and memetic MOEAs with added material on solving constrained multi-objective problems

  • Additional material on the most recent MOEA test functions and performance measures, as well as on the latest developments on the theoretical foundations of MOEAs

  • An exhaustive index and bibliography

This self-contained reference is invaluable to students, researchers and in particular to computer scientists, operational research scientists and engineers working in evolutionary computation, genetic algorithms and artificial intelligence.

 

"...If you still do not know this book, then, I urge you to run-don't walk-to your nearest on-line or off-line book purveyor and click, signal or otherwise buy this important addition to our literature."

-David E. Goldberg, University of Illinois at Urbana-Champaign

Table of contents (10 chapters)

Buy this book

eBook $89.00
price for USA (gross)
  • ISBN 978-0-387-36797-2
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $124.00
price for USA
  • ISBN 978-0-387-33254-3
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $124.00
price for USA
  • ISBN 978-1-4899-9460-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Evolutionary Algorithms for Solving Multi-Objective Problems
Authors
Series Title
Genetic and Evolutionary Computation
Copyright
2007
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-36797-2
DOI
10.1007/978-0-387-36797-2
Hardcover ISBN
978-0-387-33254-3
Softcover ISBN
978-1-4899-9460-8
Series ISSN
1932-0167
Edition Number
2
Number of Pages
XXI, 800
Topics