Second-Order Subdifferential Optimality Conditions in Nonsmooth Optimization
Abstract
The paper is devoted to deriving novel second-order necessary and sufficient optimality conditions for local minimizers in rather general classes of nonsmooth unconstrained and constrained optimization problems in finite-dimensional spaces. The established conditions are expressed in terms of second-order subdifferentials of lower semicontinuous functions and mainly concern prox-regular objectives that cover a large territory in nonsmooth optimization and its applications. Our tools are based on the machinery of variational analysis and second-order generalized differentiation. The obtained general results are applied to problems of nonlinear programming, where the derived second-order optimality conditions are new even for problems with twice continuously differential data, being expressed there in terms of the classical Hessian matrices.
Cite
@article{arxiv.2312.16277,
title = {Second-Order Subdifferential Optimality Conditions in Nonsmooth Optimization},
author = {Pham Duy Khanh and Vu Vinh Huy Khoa and Boris S. Mordukhovich and Vo Thanh Phat},
journal= {arXiv preprint arXiv:2312.16277},
year = {2025}
}