Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions

Fuente: arXiv
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Main Authors: Ghosh, Suprova, Ghosh, Debdas, Tammer, Christiane, Zhao, Xiaopeng
Format: Preprint
Published: 2025
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author Ghosh, Suprova
Ghosh, Debdas
Tammer, Christiane
Zhao, Xiaopeng
author_facet Ghosh, Suprova
Ghosh, Debdas
Tammer, Christiane
Zhao, Xiaopeng
contents In this article, we develop a trust-region technique to find critical points of unconstrained set optimization problems with the objective set-valued map defined by finitely many twice continuously differentiable functions. The technique is globally convergent and has the descent property. To ensure the descent property, a new rule of trust-region reduction ratio is introduced for the considered set-valued maps. In the derived method, to find the sequence of iteration points, we need to perform one iteration of a different vector optimization problem at each iteration. Thus, the derived technique is found to be not a straight extension of that for vector optimization. The effectiveness of the proposed algorithm is reported through performance profiles of the proposed approach with the existing methods on various test examples. A list of test problems for set optimization is also provided.
format Preprint
id arxiv_https___arxiv_org_abs_2509_07836
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions
Ghosh, Suprova
Ghosh, Debdas
Tammer, Christiane
Zhao, Xiaopeng
Optimization and Control
90C20, 90C30, 90C46, 49M37, 65K05
In this article, we develop a trust-region technique to find critical points of unconstrained set optimization problems with the objective set-valued map defined by finitely many twice continuously differentiable functions. The technique is globally convergent and has the descent property. To ensure the descent property, a new rule of trust-region reduction ratio is introduced for the considered set-valued maps. In the derived method, to find the sequence of iteration points, we need to perform one iteration of a different vector optimization problem at each iteration. Thus, the derived technique is found to be not a straight extension of that for vector optimization. The effectiveness of the proposed algorithm is reported through performance profiles of the proposed approach with the existing methods on various test examples. A list of test problems for set optimization is also provided.
title Trust-Region Method for Optimization of Set-Valued Maps Given by Finitely Many Functions
topic Optimization and Control
90C20, 90C30, 90C46, 49M37, 65K05
url https://arxiv.org/abs/2509.07836