Hybrid Evolutionary Algorithms

✍ Scribed by Dr. Crina Grosan, Ajith Abraham (auth.), Ajith Abraham, Dr. Crina Grosan, Professor Hisao Ishibuchi (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2007
• Tongue: English
• Leaves: 409
• Series: Studies in Computational Intelligence 75
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

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

✦ Subjects

Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)