Second-Order Optimality Conditions for Sparse Differentiable Optimization Problems via Limiting Second-Order Subdifferentials

Fuente: arXiv
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Autores principales: Huyen, Luu Thi Thu, Jiao, Liguo, Van Tuyen, Nguyen
Formato: Preprint
Publicado: 2026
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author Huyen, Luu Thi Thu
Jiao, Liguo
Van Tuyen, Nguyen
author_facet Huyen, Luu Thi Thu
Jiao, Liguo
Van Tuyen, Nguyen
contents In this paper, we investigate a class of sparse optimization problems in which both the objective and constraint functions are Fréchet differentiable and possess locally Lipschitz continuous gradient mappings. More precisely, by utilizing the limiting (Mordukhovich) second-order subdifferential of the associated Lagrangian function, we establish new second-order necessary and sufficient optimality conditions for local optimal solutions. The obtained results are derived under mild assumptions and extend several existing results in the literature. In addition, we apply our theoretical developments to sparse multiobjective optimization problems and derive second-order sufficient optimality conditions for efficient solutions. Several examples are also presented to demonstrate the applicability and effectiveness of the proposed results.
format Preprint
id arxiv_https___arxiv_org_abs_2606_01998
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Second-Order Optimality Conditions for Sparse Differentiable Optimization Problems via Limiting Second-Order Subdifferentials
Huyen, Luu Thi Thu
Jiao, Liguo
Van Tuyen, Nguyen
Optimization and Control
49K30, 90C30, 90C33, 49J52, 49J53, 90C29
In this paper, we investigate a class of sparse optimization problems in which both the objective and constraint functions are Fréchet differentiable and possess locally Lipschitz continuous gradient mappings. More precisely, by utilizing the limiting (Mordukhovich) second-order subdifferential of the associated Lagrangian function, we establish new second-order necessary and sufficient optimality conditions for local optimal solutions. The obtained results are derived under mild assumptions and extend several existing results in the literature. In addition, we apply our theoretical developments to sparse multiobjective optimization problems and derive second-order sufficient optimality conditions for efficient solutions. Several examples are also presented to demonstrate the applicability and effectiveness of the proposed results.
title Second-Order Optimality Conditions for Sparse Differentiable Optimization Problems via Limiting Second-Order Subdifferentials
topic Optimization and Control
49K30, 90C30, 90C33, 49J52, 49J53, 90C29
url https://arxiv.org/abs/2606.01998