Robustness Characterizations for Uncertain Optimization Problems via Image Space Analysis

Hong-Zhi Wei (), Chun-Rong Chen () and Sheng-Jie Li ()
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Hong-Zhi Wei: Shaanxi Normal University
Chun-Rong Chen: Chongqing University
Sheng-Jie Li: Chongqing University

Journal of Optimization Theory and Applications, 2020, vol. 186, issue 2, No 6, 459-479

Abstract: Abstract In this paper, by means of linear and nonlinear (regular) weak separation functions, we obtain some characterizations of robust optimality conditions for uncertain optimization problems, especially saddle point sufficient optimality conditions. Additionally, the relationships between three approaches used for robustness analysis: image space analysis, vector optimization and set-valued optimization, are discussed. Finally, an application for finding a shortest path is given to verify the validity of the results derived in this paper.

Keywords: Image space analysis; Robust optimization; Vector/set-valued optimization; Robust optimality condition; 90C31; 90C30; 90C29; 90C46 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10957-020-01709-7

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