Advances in Evolutionary Algorithms: Theory, Design And Practice Chang Wook Ahn

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See all condition definitionsopens in a new window or tab
Subject
Design
Level
Advanced
ISBN
9783540317586
Category

About this product

Product Identifiers

Publisher
Springer Berlin / Heidelberg
ISBN-10
3540317589
ISBN-13
9783540317586
eBay Product ID (ePID)
52026494

Product Key Features

Number of Pages
Xvi, 172 Pages
Publication Name
Advances in Evolutionary Algorithms : Theory, Design and Practice
Language
English
Publication Year
2006
Subject
Programming / General, Engineering (General), Intelligence (Ai) & Semantics, Applied
Type
Textbook
Subject Area
Mathematics, Computers, Technology & Engineering
Author
Chang Wook Ahn
Series
Studies in Computational Intelligence Ser.
Format
Mixed Lot

Dimensions

Item Weight
34.6 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2005-939008
Series Volume Number
18
Number of Volumes
1 vol.
Illustrated
Yes
Table Of Content
Practical Genetic Algorithms.- Real-World Application: Routing Problem.- Elitist Compact Genetic Algorithms.- Real-coded Bayesian Optimization Algorithm.- Multiobjective Real-coded Bayesian Optimization Algorithm.- Conclusions.
Synopsis
Genetic and evolutionary algorithms (GEAs) have often achieved an enviable success in solving optimization problems in a wide range of disciplines. This book provides effective optimization algorithms for solving a broad class of problems quickly, accurately, and reliably by employing evolutionary mechanisms., 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.
LC Classification Number
TA329-348

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