TY - JOUR
A2 - Zhou, Weijun
AU - Lu, Sha
AU - Wei, Zengxin
PY - 2020
DA - 2020/11/10
TI - Convergence Analysis on an Accelerated Proximal Point Algorithm for Linearly Constrained Optimization Problems
SP - 8873507
VL - 2020
AB - 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 Gu¨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 O1/k2.
SN - 1024-123X
UR - https://doi.org/10.1155/2020/8873507
DO - 10.1155/2020/8873507
JF - Mathematical Problems in Engineering
PB - Hindawi
KW -
ER -