Advances in Evolutionary Algorithms: Theory, Design and Practice

Chang Wook Ahn9783540317586, 3-540-31758-9

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.

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Table of contents :
7.3 Concluding Remarks……Page 0
Preface……Page 6
Acknowledgements……Page 8
Abbreviations……Page 9
Contents……Page 11
1 Introduction……Page 14
1.1 Motivation……Page 15
1.2 Objectives……Page 16
1.3 Outline……Page 17
2 Practical Genetic Algorithms……Page 19
3 Real-World Application: Routing Problem……Page 35
4 Elitist Compact Genetic Algorithms……Page 56
5 Real-coded Bayesian Optimization Algorithm……Page 95
6 Multiobjective Real-coded Bayesian Optimization Algorithm……Page 135
7 Conclusions……Page 162
References……Page 167
Index……Page 175