Advances in Evolutionary Algorithms: Theory, Design and Practice (Studies in Computational Intelligence (18))

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. "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. This book serves to play a decisive role in bringing forth a paradigm shift in future evolutionary computation."--Jacket Introduction....Pages 1-5 Practical Genetic Algorithms....Pages 7-22 Real-World Application: Routing Problem....Pages 23-43 Elitist Compact Genetic Algorithms....Pages 45-83 Real-coded Bayesian Optimization Algorithm....Pages 85-124 Multiobjective Real-coded Bayesian Optimization Algorithm....Pages 125-151 Conclusions....Pages 153-157 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.