A Globally Convergent Sequential Quadratic Programming Algorithm for Mathematical Programs with Linear Complementarity Constraints

被引：0
|
作者：
Masao Fukushima
Zhi-Quan Luo
Jong-Shi Pang
机构：
[1] Kyoto University,Department of Applied Mathematics and Physics, Graduate School of Engineering
[2] McMaster University,Department of Electrical and Computer Engineering
[3] Hamilton,Department of Mathematical Sciences, Whiting School of Engineering
[4] The Johns Hopkins University,undefined
来源：
Computational Optimization and Applications | 1998年 / 10卷
关键词：
mathematical programs with equilibrium constraints; sequential quadratic programming; linear complementarity;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper presents a sequential quadratic programming algorithm for computing a stationary point of a mathematical program with linear complementarity constraints. The algorithm is based on a reformulation of the complementarity condition as a system of semismooth equations by means of Fischer-Burmeister functional, combined with a classical penalty function method for solving constrained optimization problems. Global convergence of the algorithm is established under appropriate assumptions. Some preliminary computational results are reported.
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页码：5 / 34
页数：29
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