Weak sharp minima revisited, Part III: error bounds for differentiable convex inclusions

• 成果类型: Article; Proceedings Paper
• 署名作者: Burke, James V.; Deng, Sien
• 署名单位: University of Washington; University of Washington Seattle; Northern Illinois University
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-007-0130-8
• 发表日期: 2009
• 页码: 37-56
• 关键词: constraint qualifications; linear regularity; metric regularity; calmness; systems

摘要

The notion of weak sharp minima unifies a number of important ideas in optimization. Part I of this work provides the foundation for the theory of weak sharp minima in the infinite-dimensional setting. Part II discusses applications of these results to linear regularity and error bounds for nondifferentiable convex inequalities. This work applies the results of Part I to error bounds for differentiable convex inclusions. A number of standard constraint qualifications for such inclusions are also examined.