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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