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Cover for 9780306467622 Cover for 9780387332543 Cover for 9789812561060 Cover for 9780070305007
The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others. Many powerful and deterministic and stochastic techniques for solving these large dimensional optimization problems have risen out of operations research, decision science, engineering, computer science and other related disciplines. The explosion in computing power continues to arouse extraordinary interest in stochastic search algorithms that require high computational speed and very large memories. A generic stochastic approach is that of evolutionary algorithms (EA). Such algorithms have been demonstrated to be very powerful and generally applicable for solving different single objective problems. Their fundamental algorithmic structures can also be applied to solving many multi-objective problems. In this book, the various features of multi-objective evolutionary algorithms (MOEAs) are presented in an innovative and unique fashion, with detailed customized forms suggested for a variety of applications. Also, extensive MOEA discussion questions and possible research directions are presented at the end of each chapter. For additional information and supplementary teaching materials, please visit the authors' website at http://www.cs.cinvestav.mx/~EVOCINV/bookinfo.html.

Hardcover:

9780306467622 | Plenum Pub Corp, June 1, 2002, cover price $245.00 | About this edition: The solving of multi-objective problems (MOPs) has been a continuing effort by humans in many diverse areas, including computer science, engineering, economics, finance, industry, physics, chemistry, and ecology, among others.

Paperback:

9781489994608 | 2 edition (Springer-Verlag New York Inc, October 28, 2014), cover price $124.00

cover image for 9780387332543
Product Description: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research...read more

Hardcover:

9780387332543 | 2 edition (Springer-Verlag New York Inc, September 7, 2007), cover price $124.00 | About this edition: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom.

cover image for 9789812561060
Product Description: This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications...read more
By Carlos A. Coello (editor) and Gary B. Lamont (editor)

Hardcover:

9789812561060 | World Scientific Pub Co Inc, December 31, 2004, cover price $272.00 | About this edition: This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs).

cover image for 9780070305007
Product Description: This comprehensive treatment of digital control theory emphasizes the incorporation of discrete modern controls. The second edition contains material in the following areas W-Transformation Design Methods, Frequency Domain Design Techniques, Robotics Applications, Modern Technology for Digital Control Implementation, and CAD Packages for Control...read more (view table of contents, read Amazon.com's description)

Hardcover:

9780070305007 | 2 sub edition (McGraw-Hill College, November 1, 1991), cover price $117.90 | About this edition: This comprehensive treatment of digital control theory emphasizes the incorporation of discrete modern controls.

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