A Unified Characterization of Multiobjective Robustness via Separation

This paper focuses on a unified approach to characterizing different kinds of multiobjective robustness concepts. Based on linear and nonlinear scalarization results for several set order relations, together with the help of image space analysis, some suitable subsets of scalarization image space ar...

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Veröffentlicht in:Journal of optimization theory and applications Jg. 179; H. 1; S. 86 - 102
Hauptverfasser: Wei, Hong-Zhi, Chen, Chun-Rong, Li, Sheng-Jie
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.10.2018
Springer Nature B.V
Schlagworte:
Applications of Mathematics
Calculus of Variations and Optimal Control; Optimization
Engineering
Mathematical programming
Mathematics
Mathematics and Statistics
Multiple objective analysis
Operations Research/Decision Theory
Optimization
Robustness
Theory of Computation
90C31
Uncertain multiobjective optimization
90C30
90C29
Robustness
Linear and nonlinear scalarization
Set order relations
Image space analysis
ISSN:0022-3239, 1573-2878
Online-Zugang:Volltext
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Zusammenfassung:This paper focuses on a unified approach to characterizing different kinds of multiobjective robustness concepts. Based on linear and nonlinear scalarization results for several set order relations, together with the help of image space analysis, some suitable subsets of scalarization image space are introduced to make equivalent characterizations for upper set (lower set, set, certainly, respectively) less ordered robustness for uncertain multiobjective optimization problems. In particular, the nonlinear scalarization functional plays a significant role in computing various multiobjective robust solutions. Finally, the corresponding examples are included to show the effectiveness of the results derived in this paper.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-017-1196-y