Error bounds revisited. (3rd April 2022)

• Record Type: Journal Article
• Authors: Cuong, Nguyen Duy; Kruger, Alexander Y.
• Is Part Of: Optimization. Volume 71:Number 4(2022)
• Page Start: 1021
• Page End: 1053
• Publication Date: 2022-04-03
• Subjects: Error bound -- slope -- subdifferential -- subregularity -- semi-infinite programming; 49J52 -- 49J53 -- 49K40 -- 90C30 -- 90C46; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2022.2032695
• Languages: English
• ISSNs: 0233-1934

Abstract

Abstract : We propose a unifying general framework of quantitative primal and dual sufficient and necessary error bound conditions covering linear and nonlinear, local and global settings. The function is not assumed to possess any particular structure apart from the standard assumptions of lower semicontinuity in the case of sufficient conditions and (in some cases) convexity in the case of necessary conditions. We expose the roles of the assumptions involved in the error bound assertions, in particular, on the underlying space: general metric, normed, Banach or Asplund. Employing special collections of slope operators, we introduce a succinct form of sufficient error bound conditions, which allows one to combine in a single statement several different assertions: nonlocal and local primal space conditions in complete metric spaces, and subdifferential conditions in Banach and Asplund spaces.