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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Published in:Journal of optimization theory and applications Vol. 179; no. 1; pp. 86 - 102
Main Authors: Wei, Hong-Zhi, Chen, Chun-Rong, Li, Sheng-Jie
Format: Journal Article
Language:English
Published: New York Springer US 01.10.2018
Springer Nature B.V
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ISSN:0022-3239, 1573-2878
Online Access:Get full text
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Summary: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.
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ISSN:0022-3239
1573-2878
DOI:10.1007/s10957-017-1196-y