Evolutionary Multiobjective Optimization
Theoretical Advances and Applications
Published on 22. October 2010
Book
Paperback/Softback
XVIII, 302 pages
978-1-84996-916-1 (ISBN)
Description
Evolutionary Multi-Objective Optimization is an expanding field of research. This book brings a collection of papers with some of the most recent advances in this field. The topic and content is currently very fashionable and has immense potential for practical applications and includes contributions from leading researchers in the field. Assembled in a compelling and well-organised fashion, Evolutionary Computation Based Multi-Criteria Optimization will prove beneficial for both academic and industrial scientists and engineers engaged in research and development and application of evolutionary algorithm based MCO. Packed with must-find information, this book is the first to comprehensively and clearly address the issue of evolutionary computation based MCO, and is an essential read for any researcher or practitioner of the technique.
More details
Series
Edition
Softcover reprint of hardcover 1st ed. 2005
Language
English
Place of publication
London
United Kingdom
Target group
Professional and scholarly
Research
Illustrations
XVIII, 302 p.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 18 mm
Weight
487 gr
ISBN-13
978-1-84996-916-1 (9781849969161)
DOI
10.1007/1-84628-137-7
Schweitzer Classification
Other editions
Additional editions
Ajith Abraham | Robert Goldberg
Evolutionary Multiobjective Optimization
Theoretical Advances and Applications
Book
05/2005
Springer
€192.59
Shipment within 15-20 days
Content
Evolutionary Multiobjective Optimization.- Recent Trends in Evolutionary Multiobjective Optimization.- Self-adaptation and Convergence of Multiobjective Evolutionary Algorithms in Continuous Search Spaces.- A Simple Approach to Evolutionary Multiobjective Optimization.- Quad-trees: A Data Structure for Storing Pareto Sets in Multiobjective Evolutionary Algorithms with Elitism.- Scalable Test Problems for Evolutionary Multiobjective Optimization.- Particle Swarm Inspired Evolutionary Algorithm (PS-EA) for Multi-Criteria Optimization Problems.- Evolving Continuous Pareto Regions.- MOGADES: Multi-Objective Genetic Algorithm with Distributed Environment Scheme.- Use of Multiobjective Optimization Concepts to Handle Constraints in Genetic Algorithms.- Multi-criteria Optimization of Finite State Automata: Maximizing Performance while Minimizing Description Length.- Multiobjective Optimization of Space Structures under Static and Seismic Loading Conditions.