Multi-Objective Memetic Algorithms

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Chi-Keong Goh, Yew Soon Ong, Kay Chen Tan
Springer Science & Business Media, Feb 26, 2009 - Mathematics - 404 pages

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 counterparts. Nonetheless, researchers are only beginning to realize the vast potential of multi-objective Memetic algorithm and there remain many open topics in its design.

This book presents a very first comprehensive collection of works, written by leading researchers in the field, and reflects the current state-of-the-art in the theory and practice of multi-objective Memetic algorithms. "Multi-Objective Memetic algorithms" is organized for a wide readership and will be a valuable reference for engineers, researchers, senior undergraduates and graduate students who are interested in the areas of Memetic algorithms and multi-objective optimization.

 

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Contents

Evolutionary MultiMultiObjective Optimization EMMOO
3
This necessitates the consideration of multiple MO problems simultaneously
27
Problem Case Study by Ishibuchi et al discuss the various implementation
44
Knowledge infused in design of problemspecific operators
50
Dipti Srinivasan Zhang Hua 53
71
Application of Evolutionary Algorithms for Solving
90
Lee Loo Hay Chew Ek Peng Teng suyan Li juxin 91
111
MultiObjective Robust Optimization Assisted by Response
133
Hybrid BehavioralBased Multiobjective Space Trajectory
231
NatureInspired Particle Mechanics Algorithm
254
In Combination of Genetic Algorithms and Evolution Strategies with Self
279
Comparison between MOEAD and NSGAII on
309
Integrating CrossDominance Adaptation in MultiObjective
325
A Memetic Algorithm for Dynamic Multiobjective
352
A Memetic Coevolutionary MultiObjective Differential
369
Multiobjective Memetic Algorithm and Its Application
389

Multiobjective MetamodelAssisted Memetic Algorithms
152
A Convergence Acceleration Technique for Multiobjective
183
The first article Risk and Cost Tradeoff In Economic Dispatch Including
209
which incorporates a simulated annealing algorithm as the local search operator
393
Author Index
403
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