Convergence of distributed approximate subgradient method for minimizing convex function with convex functional constraints

被引:0
|
作者
Pioon, Jedsadapong [1 ]
Petrot, Narin [2 ,3 ]
Nimana, Nimit [1 ]
机构
[1] Khon Kaen Univ, Fac Sci, Dept Math, Khon Kaen 40002, Thailand
[2] Naresuan Univ, Fac Sci, Dept Math, Phitsanulok 65000, Thailand
[3] Naresuan Univ, Fac Sci, Ctr Excellence Nonlinear Anal & Optimizat, Phitsanulok 65000, Thailand
来源
AIMS MATHEMATICS | 2024年 / 9卷 / 07期
关键词
approximate subgradient; subgradient method; convex; convergence; OPTIMIZATION; ALGORITHMS;
D O I
10.3934/math.2024934
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we investigate the distributed approximate subgradient-type method for minimizing a sum of differentiable and non-differentiable convex functions subject to nondifferentiable convex functional constraints in a Euclidean space. We establish the convergence of the sequence generated by our method to an optimal solution of the problem under consideration. Moreover, we derive a convergence rate of order O(N1-a) for the objective function values, where a E (0.5, 1). Finally, we provide a numerical example illustrating the effectiveness of the proposed method.
引用
收藏
页码:19154 / 19175
页数:22
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