Strong Convergence of Modified Algorithms Based on the Regularization for the Constrained Convex Minimization Problem. (27th October 2014)

• Record Type: Journal Article
• Authors: Tian, Ming; Gong, Jun-Ying
• Other Names: Hämarik Uno Academic Editor.
• Is Part Of: Abstract and applied analysis. Volume 2014(2014)
• Publication Date: 2014-10-27
• Subjects: Mathematical analysis -- Periodicals; Mathematical analysis; Applied Mathematics; Mathematical Analysis; Periodicals; 515.05
• DOI: 10.1155/2014/870102
• Languages: English
• ISSNs: 1085-3375

Abstract

Abstract : As is known, the regularization method plays an important role in solving constrained convex minimization problems. Based on the idea of regularization, implicit and explicit iterative algorithms are proposed in this paper and the sequences generated by the algorithms can converge strongly to a solution of the constrained convex minimization problem, which also solves a certain variational inequality. As an application, we also apply the algorithm to solve the split feasibility problem.