Hybrid Evolutionary Algorithms

By: Crina Grosan (Editor), Ajith Abraham (Editor), Hisao Ishibuchi (Editor)

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Hardcover | 19 September 2007

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Hardcover
420 Pages

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23.39 x 15.6 x 2.39

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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.

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You Can Find This Book In

Non-Fiction Computing & I.T.Computer Programming & Software Development Algorithms & Data Structures Computer Science Artificial Intelligence Neural Networks & Fuzzy Systems Graphical & Digital Media Applications Computer-Aided Design CAD Mathematics Applied Mathematics Engineering & Technology

Technology in General Maths for Engineers Engineering in General

Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews	p. 1
Quantum-Inspired Evolutionary Algorithm for Numerical Optimization	p. 19
Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective	p. 39
Hybrid Evolutionary Algorithms and Clustering Search	p. 77
A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy	p. 101
An Efficient Nearest Neighbor Classifier	p. 127
Hybrid Genetic: Particle Swarm Optimization Algorithm	p. 147
A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection	p. 171
Memetic Algorithms Parametric Optimization for Microlithography	p. 201
Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction	p. 241
A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids	p. 269
Clustering Gene-Expresslon Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search	p. 313
Robust Parametric Image Registration	p. 337
Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP	p. 361
Table of Contents provided by Blackwell. All Rights Reserved.

Hybrid Evolutionary Algorithms

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Hardcover

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