A smoothing Newton method for second-order cone optimization based on a new smoothing function

被引:18
作者
Tang, Jingyong [1 ,2 ]
He, Guoping [3 ]
Dong, Li [2 ]
Fang, Liang [4 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Math, Shanghai 200240, Peoples R China
[2] Xinyang Normal Univ, Coll Math & Informat Sci, Xinyang 464000, Peoples R China
[3] Shandong Univ Sci & Technol, Coll Informat Sci & Engn, Qingdao 266510, Peoples R China
[4] Taishan Univ, Coll Math & Syst Sci, Tai An 271021, Shandong, Peoples R China
基金
中国国家自然科学基金;
关键词
Second-order cone optimization; Smoothing Newton method; Global convergence; Quadratic convergence; INTERIOR-POINT ALGORITHMS; NONLINEAR COMPLEMENTARITY-PROBLEMS; CONTINUATION METHOD; CONVERGENCE;
D O I
10.1016/j.amc.2011.06.015
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A new smoothing function is given in this paper by smoothing the symmetric perturbed Fischer-Burmeister function. Based on this new smoothing function, we present a smoothing Newton method for solving the second-order cone optimization (SOCO). The method solves only one linear system of equations and performs only one line search at each iteration. Without requiring strict complementarity assumption at the SOCO solution, the proposed algorithm is shown to be globally and locally quadratically convergent. Numerical results demonstrate that our algorithm is promising and comparable to interior-point methods. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:1317 / 1329
页数:13
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