Overview
- Presents recent results in Evolutionary Multi-objective Optimization in Uncertain Environments
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 186)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (10 chapters)
-
Front Matter
-
Introduction
-
Part I: Evolving Solution Sets in the Presence of Noise
-
Front Matter
-
-
Part II: Tracking Dynamic Multi-objective Landscapes
-
Front Matter
-
-
Part III: Evolving Robust Solution Sets
-
Front Matter
-
-
Back Matter
Keywords
About this book
Evolutionary algorithms are sophisticated search methods that have been found to be very efficient and effective in solving complex real-world multi-objective problems where conventional optimization tools fail to work well. Despite the tremendous amount of work done in the development of these algorithms in the past decade, many researchers assume that the optimization problems are deterministic and uncertainties are rarely examined.
The primary motivation of this book is to provide a comprehensive introduction on the design and application of evolutionary algorithms for multi-objective optimization in the presence of uncertainties. In this book, we hope to expose the readers to a range of optimization issues and concepts, and to encourage a greater degree of appreciation of evolutionary computation techniques and the exploration of new ideas that can better handle uncertainties. "Evolutionary Multi-Objective Optimization in Uncertain Environments: Issues and Algorithms" is intended 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 evolutionary multi-objective optimization and uncertainties.
Authors and Affiliations
Bibliographic Information
Book Title: Evolutionary Multi-objective Optimization in Uncertain Environments
Book Subtitle: Issues and Algorithms
Authors: Chi-Keong Goh, Kay Chen Tan
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-540-95976-2
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2009
Hardcover ISBN: 978-3-540-95975-5Published: 09 March 2009
Softcover ISBN: 978-3-642-10113-7Published: 28 October 2010
eBook ISBN: 978-3-540-95976-2Published: 03 February 2009
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XI, 271
Topics: Computer-Aided Engineering (CAD, CAE) and Design, Mathematical and Computational Engineering, Artificial Intelligence