Advances in Evolutionary Algorithms: Theory, Design and Practice (Studies in Computational Intelligence)

Chang Wook Ahn

ISBN 10: 364206860X / ISBN 13: 9783642068607

Published by Springer, 2006

About this Item

186 pages. 9.25x6.10x0.43 inches. In Stock. Seller Inventory # x-364206860X

Bibliographic Details

Title: Advances in Evolutionary Algorithms: Theory,...

Publisher: Springer

Publication Date: 2006

Binding: Paperback

Condition: Brand New

About this title

Synopsis:

Every real-world problem from economic to scientific and engineering fields is ultimately confronted with a common task, viz., optimization. Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated:

• Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines.
• Demonstrating the practical use of the suggested road map.
• Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications.
• Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain.
• Opening an important track for multiobjective GEA research that relies on decomposition principle.

This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation.

From the Back Cover:

Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. The goal of this book is to provide effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms. In this regard, five significant issues have been investigated:

• Bridging the gap between theory and practice of GEAs, thereby providing practical design guidelines.
• Demonstrating the practical use of the suggested road map.
• Offering a useful tool to significantly enhance the exploratory power in time-constrained and memory-limited applications.
• Providing a class of promising procedures that are capable of scalably solving hard problems in the continuous domain.
• Opening an important track for multiobjective GEA research that relies on decomposition principle.

This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation.