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The rate of convergence of proximal method of multipliers for nonlinear programming.

Authors :
Zhang, Yule
Wu, Jia
Zhang, Liwei
Source :
Optimization Methods & Software. Oct2020, Vol. 35 Issue 5, p1022-1049. 28p.
Publication Year :
2020

Abstract

We analyze the rate of convergence of the proximal method of multipliers for non-convex nonlinear programming problems. First, we prove, under the strict complementarity condition, that the rate of convergence of the proximal method of multipliers is linear and the ratio constant is proportional to 1/c when the ratio ‖ (μ 0 , λ 0) − (μ ¯ , λ ¯) ‖ / c is small enough, which implies that the rate of convergence of the proximal method of multipliers is superlinear when the parameter c increases to + ∞. Second, we prove that, without strict complementarity condition, the rate of convergence of the proximal method of multipliers is proportional to 1/c when c exceeds a threshold. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10556788
Volume :
35
Issue :
5
Database :
Academic Search Index
Journal :
Optimization Methods & Software
Publication Type :
Academic Journal
Accession number :
145497896
Full Text :
https://doi.org/10.1080/10556788.2020.1738435