Overview
- Recent advances in evolutionary Algorithms
Part of the book series: Studies in Computational Intelligence (SCI, volume 18)
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Table of contents (7 chapters)
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Advances in Evolutionary Algorithms
Book Subtitle: Theory, Design and Practice
Authors: Chang Wook Ahn
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/3-540-31759-7
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2006
Hardcover ISBN: 978-3-540-31758-6Published: 02 March 2006
Softcover ISBN: 978-3-642-06860-7Published: 30 November 2010
eBook ISBN: 978-3-540-31759-3Published: 22 May 2007
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XVI, 172
Topics: Mathematical and Computational Engineering, Artificial Intelligence