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论文类型：期刊论文

发表时间：2020-09-02

发表刊物：OPTIMIZATION METHODS & SOFTWARE

收录刊物：SCIE

卷号：35

期号：5,SI

页面范围：1022-1049

ISSN号：1055-6788

关键字：Nonlinear programming; rate of convergence; proximal method of multipliers; strict complementarity

摘要：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 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.