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.
Author(s): Gideon Avigad (auth.), Chi-Keong Goh, Yew-Soon Ong, Kay Chen Tan (eds.)
Series: Studies in Computational Intelligence 171
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2009
Language: English
Pages: 404
Tags: Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics)
Front Matter....Pages -
Front Matter....Pages 1-1
Evolutionary Multi-Multi-Objective Optimization - EMMOO....Pages 3-26
Implementation of Multiobjective Memetic Algorithms for Combinatorial Optimization Problems: A Knapsack Problem Case Study....Pages 27-49
Front Matter....Pages 51-51
Solving Time-Tabling Problems Using Evolutionary Algorithms and Heuristics Search....Pages 53-69
An Efficient Genetic Algorithm with Uniform Crossover for the Multi-Objective Airport Gate Assignment Problem....Pages 71-89
Application of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimization Problems....Pages 91-110
Feature Selection Using Single/Multi-Objective Memetic Frameworks....Pages 111-131
Multi-Objective Robust Optimization Assisted by Response Surface Approximation and Visual Data-Mining....Pages 133-151
Multiobjective Metamodel–Assisted Memetic Algorithms....Pages 153-181
A Convergence Acceleration Technique for Multiobjective Optimisation....Pages 183-205
Front Matter....Pages 207-207
Risk and Cost Tradeoff in Economic Dispatch Including Wind Power Penetration Based on Multi-Objective Memetic Particle Swarm Optimization....Pages 209-230
Hybrid Behavioral-Based Multiobjective Space Trajectory Optimization....Pages 231-253
Nature-Inspired Particle Mechanics Algorithm for Multi-Objective Optimization....Pages 255-277
Front Matter....Pages 279-279
Combination of Genetic Algorithms and Evolution Strategies with Self-adaptive Switching....Pages 281-307
Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem....Pages 309-324
Integrating Cross-Dominance Adaptation in Multi-Objective Memetic Algorithms....Pages 325-351
A Memetic Algorithm for Dynamic Multiobjective Optimization....Pages 353-367
A Memetic Coevolutionary Multi-Objective Differential Evolution Algorithm....Pages 369-388
Multiobjective Memetic Algorithm and Its Application in Robust Airfoil Shape Optimization....Pages 389-402
Back Matter....Pages -
