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Multi-objective memetic algorithms

Author: Chi-Keong Goh; Yew Soon Ong; K C Tan
Publisher: Berlin ; London : Springer, 2009.
Series: Studies in computational intelligence, 171.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories, having demonstrated better efficacy in dealing with multi-objective problems as compared to its conventional  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Multi-objective memetic algorithms.
Berlin ; London : Springer, 2009
(OCoLC)269435324
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Chi-Keong Goh; Yew Soon Ong; K C Tan
ISBN: 9783540880516 3540880518 354088050X 9783540880509
OCLC Number: 314175016
Description: 1 online resource.
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, 171.
Responsibility: edited by Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan.

Abstract:

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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