Convergence of a penalty method for mathematical programming with complementarity constraints

被引：150

作者：

Hu, XM ^{[1
]}

Ralph, D

机构：

[1] CSIRO Mfg & Infrastruct Technol, Sydney, NSW, Australia

[2] Univ Cambridge, Cambridge, England

来源：

JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS | 2004年 / 123卷 / 02期

基金：

澳大利亚研究理事会;

关键词：

complementarity constraints; penalty methods; B-stationarity; linear independence constraint qualification;

D O I：

10.1007/s10957-004-5154-0

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 [运筹学与控制论]; 12 [管理学]; 1201 [管理科学与工程]; 1202 [工商管理学]; 120202 [企业管理];

摘要：

We adapt the convergence analysis of the smoothing (Ref. 1) and regularization ( Ref. 2) methods to a penalty framework for mathematical programs with complementarity constraints (MPCC); we show that the penalty framework shares convergence properties similar to those of these methods. Moreover, we give sufficient conditions for a sequence generated by the penalty framework to be attracted to a B-stationary point of the MPCC.

引用

页码：365 / 390

页数：26

共 18 条

[1]

Bertsekas D., 2019, Reinforcement Learning and Optimal Control

[2]

Chen Y., 1995, Optimization, V32, P193, DOI 10.1080/02331939508844048

[3]

A smoothing method for mathematical programs with equilibrium constraints [J].