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Sequential Approximate Multiobjective Optimization Using Computational Intelligence

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... Full description

1st Person: Nakayama, Hirotaka
Additional Corporate Bodies: SpringerLink (Online service)
Additional Persons: Yun, Yeboon [author]; Yoon, Min [author]
Type of Publication: Book
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2009, 2009
Edition: 1st ed. 2009
Series: Vector Optimization
Keywords: Theory of Computation
Mathematical Modeling and Industrial Mathematics
Operations research
Information theory
Operations Research, Management Science
Computational complexity
Optimization
Operations Research/Decision Theory
Mathematical optimization
Discrete Mathematics in Computer Science
Online: Volltext
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Summary: 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
Physical Description: XVI, 200 p. 111 illus online resource
ISBN: 9783540889106

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