Back to Search
Start Over
Convergence Analysis on an Accelerated Proximal Point Algorithm for Linearly Constrained Optimization Problems.
- Source :
- Mathematical Problems in Engineering; 11/10/2020, p1-13, 13p
- Publication Year :
- 2020
-
Abstract
- Proximal point algorithm is a type of method widely used in solving optimization problems and some practical problems such as machine learning in recent years. In this paper, a framework of accelerated proximal point algorithm is presented for convex minimization with linear constraints. The algorithm can be seen as an extension to G u ¨ ler's methods for unconstrained optimization and linear programming problems. We prove that the sequence generated by the algorithm converges to a KKT solution of the original problem under appropriate conditions with the convergence rate of O 1 / k 2 . [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 1024123X
- Database :
- Complementary Index
- Journal :
- Mathematical Problems in Engineering
- Publication Type :
- Academic Journal
- Accession number :
- 146928037
- Full Text :
- https://doi.org/10.1155/2020/8873507