Local convergence of SQP methods for mathematical programs with equilibrium constraints

被引：154

作者：

Fletcher, R ^{[1
]}

Leyffer, S

Ralph, D

Scholtes, S

机构：

[1] Univ Dundee, Dept Math, Dundee DD1 4HN, Scotland

[2] Argonne Natl Lab, Div Math & Comp Sci, Argonne, IL 60439 USA

[3] Univ Cambridge, Judge Inst, Cambridge CB2 1AG, England

来源：

SIAM JOURNAL ON OPTIMIZATION | 2006年 / 17卷 / 01期

关键词：

nonlinear programming; sequential quadratic programming (SQP); mathematical programs with equilibrium constraints (MPEC); mathematical programs with complementarity constraints (MPCC); equilibrium constraints;

D O I：

10.1137/S1052623402407382

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Recently, nonlinear programming solvers have been used to solve a range of mathematical programs with equilibrium constraints (MPECs). In particular, sequential quadratic programming (SQP) methods have been very successful. This paper examines the local convergence properties of SQP methods applied to MPECs. SQP is shown to converge superlinearly under reasonable assumptions near a strongly stationary point. A number of examples are presented that show that some of the assumptions are difficult to relax.

引用

页码：259 / 286

页数：28

共 22 条

[1] Global convergence of an elastic mode approach for a class of mathematical programs with complementarity constraints [J].