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Hybrid evolutionary algorithms / Crina Grosan, Ajith Abraham, Hisao Ishibuchi (eds.).

By: Contributor(s): Material type: TextTextLanguage: English Series: Studies in computational intelligence ; 75Publication details: Berlin ; New York : Springer, 2007.Description: xv, 403 p. : ill. ; 25 cmISBN:
  • 9783540732969
Subject(s): DDC classification:
  • 005.1 22 ABR
Online resources:
Contents:
Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews Quantum-Inspired Evolutionary Algorithm for Numerical Optimization Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective Hybrid Evolutionary Algorithms and Clustering Search A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy An Efficient Nearest Neighbor Classifier Hybrid Genetic: Particle Swarm Optimization Algorithm A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection Memetic Algorithms Parametric Optimization for Microlithography Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search Robust Parametric Image Registration Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP.
Summary: "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 Read more...
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Reference Books Reference Books CUTN Central Library Reference Reference 005.1 ABR (Browse shelf(Opens below)) Not For Loan 37197

Hybrid Evolutionary Algorithms: Methodologies, Architectures, and Reviews
Quantum-Inspired Evolutionary Algorithm for Numerical Optimization
Enhanced Evolutionary Algorithms for Multidisciplinary Design Optimization: A Control Engineering Perspective
Hybrid Evolutionary Algorithms and Clustering Search
A Novel Hybrid Algorithm for Function Optimization: Particle Swarm Assisted Incremental Evolution Strategy
An Efficient Nearest Neighbor Classifier
Hybrid Genetic: Particle Swarm Optimization Algorithm
A Hybrid Genetic Algorithm and Bacterial Foraging Approach for Global Optimization and Robust Tuning of PID Controller with Disturbance Rejection
Memetic Algorithms Parametric Optimization for Microlithography
Significance of Hybrid Evolutionary Computation for Ab Initio Protein Folding Prediction
A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids
Clustering Gene-Expression Data: A Hybrid Approach that Iterates Between k-Means and Evolutionary Search
Robust Parametric Image Registration
Pareto Evolutionary Algorithm Hybridized with Local Search for Biobjective TSP.


"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 Read more...

Includes bibliographical references and index.

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