A globally and superlinearly convergent modified SQP-filter method

被引：0
作者：
Ke Su
机构：
[1] Tongji University,Department of Mathematics
[2] Hebei University,College of Mathematics and Computer
来源：
Journal of Global Optimization | 2008年 / 41卷
关键词：
Constrained optimization; KKT point; Sequential quadratic programming; Global convergence; Superlinear convergence;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, we presented a modified SQP-filter method based on the modified quadratic subproblem proposed by Zhou (J. Global Optim. 11, 193–2005, 1997). In contrast with the SQP methods, each iteration this algorithm only needs to solve one quadratic programming subproblems and it is always feasible. Moreover, it has no demand on the initial point. With the filter technique, the algorithm shows good numerical results. Under some conditions, the globally and superlinearly convergent properties are given.
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页码：203 / 217
页数：14
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