Optimality Conditions at Infinity in Semialgebraic Vector Optimization

We are interested in optimality conditions for semialgebraic vector optimization problems with a situation in which generalized (weakly) nondominated points do exist but are not attained as image points of (weakly) efficient solutions. To this end, cones associated with unbounded semialgebraic sets at infinity are introduced and studied. Then, optimality conditions at infinity in terms of the Newton polyhedra of the objective mappings and of the cones associated with the constraint sets at infinity for the problems in question are proposed. Funding: L. Jiao was partially supported by the Chinese National Natural Science Foundation [Grant 12371300]. J. H. Lee was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [Grant NRF-2021R1C1C2004488]. T.-S. Pham was supported by the Vietnam National Foundation for Science and Technology Development (NAFOSTED) [Grant 101.04-2023.06].

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Publication Details

Journal
Mathematics of Operations Research
Published
2025-08-11
DOI
https://doi.org/10.1287/moor.2024.0607
Primary Topic
Optimization and Variational Analysis
Type
article
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Optimality Conditions at Infinity in Semialgebraic Vector Optimization

Jae Hyoung Lee, Tiến-Sơn Phạm, Liguo Jiao
Mathematics of Operations Research
Optimization and Variational Analysis
article

Optimality Conditions at Infinity in Semialgebraic Vector Optimization

Jae Hyoung Lee, Tiến-Sơn Phạm, Liguo Jiao
article en

Abstract

We are interested in optimality conditions for semialgebraic vector optimization problems with a situation in which generalized (weakly) nondominated points do exist but are not attained as image points of (weakly) efficient solutions. To this end, cones associated with unbounded semialgebraic sets at infinity are introduced and studied. Then, optimality conditions at infinity in terms of the Newton polyhedra of the objective mappings and of the cones associated with the constraint sets at infinity for the problems in question are proposed. Funding: L. Jiao was partially supported by the Chinese National Natural Science Foundation [Grant 12371300]. J. H. Lee was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) [Grant NRF-2021R1C1C2004488]. T.-S. Pham was supported by the Vietnam National Foundation for Science and Technology Development (NAFOSTED) [Grant 101.04-2023.06].

Mathematics of Operations Research
Northeast Normal University (CN), Dalat University (VN), Pukyong National University (KR)
Openalex Percentile: Top 78%
Optimization and Variational Analysis
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