A nonlinear norm-relaxed method for finely discretized semi-infinite optimization problems

被引：5
|
作者：
Xu, Qing-Juan [1 ,2 ]
Jian, Jin-Bao [3 ,4 ]
机构：
[1] Shanghai Univ, Dept Math Sci, Shanghai 200444, Peoples R China
[2] Guangxi Teachers Educ Univ, Coll Math Sci, Nanning 530001, Guangxi, Peoples R China
[3] Yulin Normal Univ, Coll Math & Informat Sci, Yulin 537000, Guangxi, Peoples R China
[4] Guangxi Univ, Coll Math & Informat Sci, Nanning 530004, Guangxi, Peoples R China
来源：
NONLINEAR DYNAMICS | 2013年 / 73卷 / 1-2期
基金：
中国国家自然科学基金;
关键词：
Semi-infinite optimization; QCQP; Norm-relaxed method; Global convergence; QUADRATIC-PROGRAMMING METHOD; FEASIBLE DIRECTIONS; ALGORITHM;
D O I：
10.1007/s11071-013-0768-0
中图分类号：
TH [机械、仪表工业];
学科分类号：
0802 ;
摘要：
In this paper, we present a sequential simple quadratically constrained quadratic programming (QCQP) norm-relaxed method for finely discretized semi-infinite optimization problems. At each iteration, the iteration point is feasible, and an improved search direction is solved by only one simple QCQP subproblem, in which only a few of constraints are chosen. Under some weak conditions, the proposed algorithm possesses weak global convergence. Finally, numerical results show that the proposed method is effective.
引用
收藏
页码：85 / 92
页数：8
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