Minimax programming as a tool for studying robust multi-objective optimization problems

Zhe Hong (), Kwan Deok Bae () and Do Sang Kim ()
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Zhe Hong: Yanbian University
Kwan Deok Bae: Pukyong National University
Do Sang Kim: Pukyong National University

Annals of Operations Research, 2022, vol. 319, issue 2, No 6, 1589-1606

Abstract: Abstract This paper aims to investigate optimality conditions for a weakly Pareto solution to a robust multi-objective optimization problem with locally Lipschitzian data. We do this by using a minimax programming approach, namely, by establishing the necessary optimality condition for a (local) optimal solution to a robust minimax optimization problem under a suitable constraint qualification, we then employ it to arrive in the desired target. In addition, some duality results for both robust minimax optimization problems and robust multi-objective optimization problems are also provided.

Keywords: Multi-objective optimization; Minimax programming; Generalized convexity; KKT optimality conditions; Duality; 90C25; 90C46 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10479-021-04179-w

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