
Applications Of Multi-objective Evolutionary Algorithms
World Scientific Publishing Co Pte Ltd
Will be published approx. on 9. December 2004
Book
Hardback
792 pages
978-981-256-106-0 (ISBN)
Description
This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 234 mm
Width: 161 mm
Thickness: 44 mm
Weight
1211 gr
ISBN-13
978-981-256-106-0 (9789812561060)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Author
Cinvestav-ipn, Mexico
Air Force Inst Of Technology, Usa
Content
An Introduction to Multi-Objective Evolutionary Algorithms and Their Applications; Optimal Design of Industrial Electromagnetic Devices: A Multiobjective Evolutionary Approach; Using a Particle Swarm Optimizer with a Multi-Objective Selection Scheme to Design Combinational Logic Circuits; Automatic Control System Design via a Multiobjective Evolutionary Algorithm; Evolutionary Multi-Objective Optimization of Trusses; A Multi-Objective Evolutionary Algorithm for the Covering Tour Problem; Multiobjective Aerodynamic Design and Visualization of Supersonic Wings by Using Adaptive Range Multiobjective Genetic Algorithms; Mutli-Objective Spectroscopic Data Analysis of Inertial Confinement Fusion Implosion Cores: Plasma Gradient Determination; On Machine Learning with Multiobjective Genetic Optimization; and other papers.