AN SQP METHOD BASED ON SMOOTHING PENALTY FUNCTION FOR NONLINEAR OPTIMIZATION WITH INEQUALITY CONSTRAINT

被引：14

作者：

ZHANG Juliang ZHANG Xiangsun Institute of Applied Mathematics Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China ^{[100080
]}

机构：

来源：

JournalofSystemsScienceandComplexity | 2001年 / 02期

关键词：

D O I：

暂无

中图分类号：

O224 [最优化的数学理论];

学科分类号：

070105 [运筹学与控制论];

摘要：

In this paper, we use the smoothing penalty function proposed in [1] as the merit function of SQP method for nonlinear optimization with inequality constraints. The global convergence of the method is obtained.

引用

页码：212 / 217

页数：6

共 3 条

[1]

Robust Recursive Quadratic Programming Algorithm Model with Global and Superlinear Convergence Properties[J] F. Facchinei Journal of Optimization Theory and Applications 1997, 3

[2]

Smoothing methods for convex inequalities and linear complementarity problems [J].

Chen, CH ;

Mangasarian, OL .

MATHEMATICAL PROGRAMMING, 1995, 71 (01) :51-69

[3]

不等式约束最优化的非光滑精确罚函数的一个光滑近似 [J].

张菊亮 ;

章祥荪 .

系统科学与数学, 2000, (04) :499-505

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