This book highlights a new direction of multiobjective optimzation, which has never been treated in previous publications. When the function form of objective functions is not known explicitly as encountered in many practical problems, sequential approximate optimization based on metamodels is an effective tool from a practical viewpoint. Several sophisticated methods for sequential approximate multiobjective optimization using computational intelligence are introduced along with real applications, mainly engineering problems, in this book.
Author(s): Min Yoon, Yeboon Yun, Hirotaka Nakayama (auth.)
Series: Vector Optimization
Edition: 1
Publisher: Springer-Verlag Berlin Heidelberg
Year: 2009
Language: English
Pages: 200
Tags: Discrete Mathematics in Computer Science; Optimization; Operations Research/Decision Theory
Front Matter....Pages 1-14
Basic Concepts of Multi-objective Optimization....Pages 1-15
Interactive Programming Methods for Multi-objective Optimization....Pages 17-43
Generation of Pareto Frontier by Genetic Algorithms....Pages 45-71
Multi-objective Optimization and Computational Intelligence....Pages 73-112
Sequential Approximate Optimization....Pages 113-149
Combining Aspiration Level Approach and SAMO....Pages 151-168
Engineering Applications....Pages 169-183
Back Matter....Pages 1-13
