281. Subdifferential conditions for sharp and approximate solutions in nonsmooth optimization
Invited abstract in session MD-3: Variational Methods in Set and Vector Optimization, stream Multiobjective and Vector Optimization.
Monday, 16:30-18:30Room: B100/4011
Authors (first author is the speaker)
| 1. | Marius Durea
|
| Mathematics, University Al. I. Cuza and Octav Mayer Institute of Mathematics |
Abstract
We present new results on optimality conditions for constrained scalar and set-valued nonsmooth optimization problems, with a focus on sharp, isolated, and approximate solutions. Utilizing various types of subgradients, coderivatives, and Shapiro properties for sets, we characterize different degrees of sharpness and extend existing results from the literature. Additionally, we explore approximate minimality for the same class of problems and establish necessary conditions under mild assumptions on the objective function. Our findings provide new insights into certain optimality conditions in nonsmooth optimization and further expand the existing theoretical framework.
Keywords
- Non-smooth optimization
- First-order optimization
Status: accepted
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