A penalty-free method with line search for nonlinear equality constrained optimization

被引:8
作者
Ge, Hengwu [1 ]
Chen, Zhongwen [1 ]
机构
[1] Soochow Univ, Sch Math Sci, Suzhou 215006, Peoples R China
关键词
Equality constraints; Line search; Penalty function; Filter; Convergence analysis and rate of; convergence; TRUST-REGION METHOD; GLOBAL CONVERGENCE; FILTER ALGORITHM; LOCAL CONVERGENCE;
D O I
10.1016/j.apm.2013.05.037
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A new line search method is introduced for solving nonlinear equality constrained optimization problems. It does not use any penalty function or a filter. At each iteration, the trial step is determined such that either the value of the objective function or the measure of the constraint violation is sufficiently reduced. Under usual assumptions, it is shown that every limit point of the sequence of iterates generated by the algorithm is feasible, and there exists at least one limit point that is a stationary point for the problem. A simple modification of the algorithm by introducing second order correction steps is presented. It is shown that the modified method does not suffer from the Maratos' effect, so that it converges superlinearly. The preliminary numerical results are reported. (C) 2013 Elsevier Inc. All rights reserved.
引用
收藏
页码:9934 / 9949
页数:16
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