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Multi-objective memetic algorithms

Author: Chi-Keong Goh; Yew Soon Ong; K C Tan
Publisher: Berlin : Springer, ©2009.
Series: Studies in computational intelligence, v. 171.
Edition/Format:   Print book : EnglishView all editions and formats
Publication:SpringerLink OhioLINK electronic book center (Online)
Summary:

Memetic algorithms are a success story in sophisticated evolutionary computing. Written for as wide a readership as possible, this book reflects the current state-of-the-art in the theory and  Read more...

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Genre/Form: Electronic books
Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Chi-Keong Goh; Yew Soon Ong; K C Tan
ISBN: 9783540880509 354088050X 3540880518 9783540880516 3642099785 9783642099786
OCLC Number: 269435324
Description: xii, 402 pages : illustrations ; 24 cm.
Contents: Evolutionary Multi-Multi-Objective Optimization - EMMOO.- Implementation of Multiobjective Memetic Algorithms for Combinatorial Optimization Problems: A Knapsack Problem Case Study.- Knowledge Infused in Design of Problem-Specific Operators.- Solving Time-Tabling Problems Using Evolutionary Algorithms and Heuristics Search.- An Efficient Genetic Algorithm with Uniform Crossover for the Multi-Objective Airport Gate Assignment Problem.- Application of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimization Problems.- Feature Selection Using Single/Multi-Objective Memetic Frameworks.- Multi-Objective Robust Optimization Assisted by Response Surface Approximation and Visual Data-Mining.- Multiobjective Metamodel-Assisted Memetic Algorithms.- A Convergence Acceleration Technique for Multiobjective Optimisation.- Knowledge Propagation through Cultural Evolution.- Risk and Cost Tradeoff in Economic Dispatch Including Wind Power Penetration Based on Multi-Objective Memetic Particle Swarm Optimization.- Hybrid Behavioral-Based Multiobjective Space Trajectory Optimization.- Nature-Inspired Particle Mechanics Algorithm for Multi-Objective Optimization.- Information Exploited for Local Improvement.- Combination of Genetic Algorithms and Evolution Strategies with Self-adaptive Switching.- Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem.- Integrating Cross-Dominance Adaptation in Multi-Objective Memetic Algorithms.- A Memetic Algorithm for Dynamic Multiobjective Optimization.- A Memetic Coevolutionary Multi-Objective Differential Evolution Algorithm.- Multiobjective Memetic Algorithm and Its Application in Robust Airfoil Shape Optimization.
Series Title: Studies in computational intelligence, v. 171.
Responsibility: Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan (eds.).

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