Unified Robust Necessary Optimality Conditions for Nonconvex Nonsmooth Uncertain Multiobjective Optimization

Jie Wang (), Shengjie Li () and Min Feng ()
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Jie Wang: Chongqing University
Shengjie Li: Chongqing University
Min Feng: Chongqing Jiaotong University

Journal of Optimization Theory and Applications, 2022, vol. 195, issue 1, No 9, 226-248

Abstract: Abstract This paper is concerned with nonconvex nonsmooth uncertain multiobjective optimization problems, in which the decision variable of both objective and constraint functions is defined on Banach space while uncertain parameters are defined on arbitrary nonempty (may not be compact) sets. We employ the Stone–C̆ech compactification of uncertainty sets and the upper semicontinuous regularization of original functions with respect to uncertain parameters, giving rise to unified robust necessary optimality conditions for the local robust weakly efficient solution of the considered problem. Moreover, we derive weak and strong KKT robust necessary conditions via the constraint qualification and the regularity condition, respectively. Several examples are provided to illustrate the validity of our results.

Keywords: Robust necessary optimality conditions; Nonconvex nonsmooth uncertain multiobjective optimization; Noncompact; Stone–C̆ech compactification; 90C46; 90C29; 65K10; 49K10 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10957-022-02075-2

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