Generalized lower-order penalty algorithm for solving second-order cone mixed complementarity problems

被引:3
作者
Hao, Zijun [1 ,2 ]
Wan, Zhongping [1 ]
Chi, Xiaoni [3 ]
Jin, Zheng-Fen [4 ]
机构
[1] Wuhan Univ, Sch Math & Stat, Wuhan 430072, Peoples R China
[2] North Minzu Univ, Sch Math & Informat Sci, Yinchuan 750021, Ningxia, Peoples R China
[3] Guilin Univ Elect Technol, Sch Math & Comp Sci, Guilin 541004, Peoples R China
[4] Henan Univ Sci & Technol, Sch Math & Stat, Luoyang 471023, Peoples R China
关键词
Second-order cone; Mixed complementarity problem; Generalized lower-order penalty algorithm; Exponential convergence rate; MATRIX-SPLITTING METHOD; NEWTON METHODS; CONVERGENCE; REFORMULATION;
D O I
10.1016/j.cam.2020.113168
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The second-order cone mixed complementarity problems (SOCMCPs) can directly present the KKT conditions of the second-order cone programming, and have broad range of applications. We establish the generalized lower-order penalty algorithm in this article for solving the SOCMCPs. By using the proposed algorithm, the SOCMCP is converted to asymptotic lower-order penalty equations (LOPEs). Under the assumption that the involved function possesses the xi-monotone, we show that when the penalty parameter tends to positive infinity, the solution sequence of the asymptotic LOPEs converges to the solution of the SOCMCP at an exponential rate. Numerical results are reported to examine the efficiency of the proposed algorithm. (C) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:CP8 / U20
页数:13
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