Abstract
The paper is devoted to full stability of optimal solutions in general settings of finite-dimensional optimization with applications to particular models of constrained optimization problems, including those of conic and specifically semidefinite programming. Developing a new technique of variational analysis and generalized differentiation, we derive second-order characterizations of full stability, in both Lipschitzian and Hölderian settings, and establish their relationships with the conventional notions of strong regularity and strong stability for a large class of problems of constrained optimization with twice continuously differentiable data.
| Original language | English |
|---|---|
| Pages (from-to) | 226-252 |
| Number of pages | 27 |
| Journal | Mathematics of Operations Research |
| Volume | 40 |
| Issue number | 1 |
| DOIs | |
| State | Published - 15 Feb 2015 |
Bibliographical note
Publisher Copyright:©2015 INFORMS
Keywords
- Conic programming
- Constrained optimization
- Full stability
- Generalized differentiation
- Semidefinite programming
- Strong regularity
- Strong stability
- Variational analysis
ASJC Scopus subject areas
- General Mathematics
- Computer Science Applications
- Management Science and Operations Research