Advances in Evolutionary Algorithms Theory, Design and Practice

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Edition: 1

Series: Studies in Computational Intelligence

ISBN: 3-540-31758-9, 978-3-540-31758-6

Size: 5 MB (4902274 bytes)

Pages: 180/180

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Chang Wook Ahn3-540-31758-9, 978-3-540-31758-6

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; and 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.

Table of contents :
Advances in Evolutionary Algorithms: Theory, Design and Practice……Page 2
Preface……Page 7
Acknowledgements……Page 9
Abbreviations……Page 10
Contents……Page 12
1 Introduction……Page 15
1.1 Motivation……Page 16
1.2 Objectives……Page 17
1.3 Outline……Page 18
2 Practical Genetic Algorithms……Page 20
7.3 Concluding Remarks……Page 0
3 Real-World Application: Routing Problem……Page 36
4 Elitist Compact Genetic Algorithms……Page 57
5 Real-coded Bayesian Optimization Algorithm……Page 96
6 Multiobjective Real-coded Bayesian Optimization Algorithm……Page 136
7 Conclusions……Page 163
References……Page 168
Index……Page 176

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