个人信息Personal Information
教授
博士生导师
硕士生导师
性别:女
毕业院校:大连理工大学
学位:博士
所在单位:数学科学学院
学科:运筹学与控制论
办公地点:创新园大厦B1207
电子邮箱:wujia@dlut.edu.cn
PROXIMAL POINT ALGORITHM FOR NONLINEAR COMPLEMENTARITY PROBLEM BASED ON THE GENERALIZED FISCHER-BURMEISTER MERIT FUNCTION
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论文类型:期刊论文
发表时间:2013-01-01
发表刊物:JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
收录刊物:SCIE、Scopus
卷号:9
期号:1
页面范围:153-169
ISSN号:1547-5816
关键字:Complementarity problem; proximal point algorithm; approximation criterion
摘要:This paper is devoted to the study of the proximal point algorithm for solving monotone and nonmonotone nonlinear complementarity problems. The proximal point algorithm is to generate a sequence by solving subproblems that are regularizations of the original problem. After given an appropriate criterion for approximate solutions of subproblems by adopting a merit function, the proximal point algorithm is verified to have global and superlinear convergence properties. For the purpose of solving the subproblems efficiently, we introduce a generalized Newton method and show that only one Newton step is eventually needed to obtain a desired approximate solution that approximately satisfies the appropriate criterion under mild conditions. The motivations of this paper are twofold. One is analyzing the proximal point algorithm based on the generalized Fischer-Burmeister function which includes the Fischer-Burmeister function as special case, another one is trying to see if there are relativistic change on numerical performance when we adjust the parameter in the generalized Fischer-Burmeister.