The rate of convergence of proximal method of multipliers for second-order cone optimization problems

被引:0
作者
Li Chu
Bo Wang
Liwei Zhang
Hongwei Zhang
机构
[1] Dalian University of Technology,School of Mathematical Sciences
[2] City Institute,Key Laboratory of Operations Research and Control of Universities in Fujian, College of Mathematics and Computer Science
[3] Dalian University of Technology,School of Mathematical Sciences
[4] Fuzhou University,undefined
[5] Dalian University of Technology,undefined
来源
Optimization Letters | 2021年 / 15卷
关键词
Rate of convergence; Proximal method; Second-order cone;
D O I
暂无
中图分类号
学科分类号
摘要
In this paper we consider a proximal method of multipliers (PMM) for a nonlinear second-order cone optimization problem. With the assumptions of constraint nondegeneracy, strict complementarity and second-order sufficient condition, we estimate the local convergence rate of PMM to be linear or superlinear, which depends on the strategy of parameter selection.
引用
收藏
页码:441 / 457
页数:16
相关论文
共 29 条
  • [1] Alizadeh F(2003)Second-order cone programming Math. Program. 95 3-51
  • [2] Goldfarb D(2019)A feasible direction algorithm for nonlinear second-order cone programs Optim. Method Softw. 34 1322-1341
  • [3] Canelas A(1952)Definite and semidefinite quadratic forms Econometrica 20 295-300
  • [4] Carrasco M(2012)Differentiable exact penalty functions for nonlinear second-order cone programs SIAM J. Optim. 22 1607-1633
  • [5] López J(1969)Multiplier and gradient methods J. Optim. Theory Appl. 4 303-320
  • [6] Debreu G(2009)On the local convergence of semismooth Newton methods for linear and nonlinear second-order cone programs without strict complementarity SIAM J. Optim. 20 297-320
  • [7] Fukuda E(2007)Convergence analysis of the augmented Lagrangian method for nonlinear second-order cone optimization problems Nonlinear Anal. Theory Methods Appl. 67 1359-1373
  • [8] Silva P(2008)Convergence of the augmented Lagrangian method for nonlinear optimization problems over second-order cones J. Optim. Theory Appl. 139 557-575
  • [9] Fukushima M(1973)A dual approach to solving nonlinear programming problems by unconstrained optimization Math. Program. 5 354-373
  • [10] Hestenes MR(1976)Augmented Lagrangians and applications of the proximal point algorithm in convex programming Math. Oper. Res. 1 97-116