On Optimality Conditions for Mathematical Programming Problems Based on Strong Subdifferentials
Optimization and Control
2026-04-15 v1
Abstract
We develop refined Karush-Kuhn-Tucker (KKT) and Fritz-John (FJ)-type optimality conditions for nonsmooth, nonconvex mathematical pro\-gra\-mming problems. We pay special attention in the case that the functional constraint belongs to a specific class of generalized convex functions known as strongly quasiconvex functions. After analyzing a specialized sub\-di\-ffe\-ren\-tial, named the strong subdifferential, we compute the normal cone of the supremum function in terms of such subdifferentials, and apply this result to the mathematical programming problem. We illustrate our important results by examples.
Cite
@article{arxiv.2604.12166,
title = {On Optimality Conditions for Mathematical Programming Problems Based on Strong Subdifferentials},
author = {Felipe Lara and Alberto Ramos},
journal= {arXiv preprint arXiv:2604.12166},
year = {2026}
}