Hybrid Evolutionary Algorithms (Studies in Computational Intelligence, 75)

Hybridization of evolutionary algorithms is getting popular due to their capabilities in handling several real world problems involving complexity, noisy environment, imprecision, uncertainty and vagueness. This edited volume is targeted to present the latest state-of-the-art methodologies in __’Hybrid Evolutionary Algorithms’__. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. Front Matter....Pages I-XV Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews....Pages 1-17 Quantum-Inspired Evolutionary Algorithm for Numerical Optimization....Pages 19-37 Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective....Pages 39-76 Hybrid Evolutionary Algorithms and Clustering Search....Pages 77-99 A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy....Pages 101-125 An Efficient Nearest Neighbor Classifier....Pages 127-145 Hybrid Genetic: Particle Swarm Optimization Algorithm....Pages 147-170 A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection....Pages 171-199 Memetic Algorithms Parametric Optimization for Microlithography....Pages 201-239 Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction....Pages 241-268 A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids....Pages 269-311 Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search....Pages 313-335 Robust Parametric Image Registration....Pages 337-360 Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP....Pages 361-398 Back Matter....Pages 399-403 This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms." The chapters deal with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. Overall, the book has 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. The contributions were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed. "This edited volume is targeted to present the latest state-of-the-art methodologies in Hybrid Evolutionary Algorithms. This book deals with the theoretical and methodological aspects, as well as various applications to many real world problems from science, technology, business or commerce. This volume comprises of 14 chapters including an introductory chapter giving the fundamental definitions and some important research challenges. Chapters were selected on the basis of fundamental ideas/concepts rather than the thoroughness of techniques deployed."--Jacket