An extrapolated fixed-point optimization method for strongly convex smooth optimizations

被引:0
|
作者
Rakjarungkiat, Duangdaw [1 ]
Nimana, Nimit [1 ]
机构
[1] Khon Kaen Univ, Fac Sci, Dept Math, Khon Kaen 40002, Thailand
来源
AIMS MATHEMATICS | 2024年 / 9卷 / 02期
关键词
conjugate gradient method; cutter; extrapolated method; strong convergence; strong convexity; VARIATIONAL INEQUALITY PROBLEM; STRONG-CONVERGENCE; INTERSECTION; SET;
D O I
10.3934/math.2024210
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this work, we focused on minimizing a strongly convex smooth function over the common fixed-point constraints. We proposed an extrapolated fixed-point optimization method, which is a modified version of the extrapolated sequential constraint method with conjugate gradient direction. We proved the convergence of the generated sequence to the unique solution to the considered problem without boundedness assumption. We also investigated some numerical experiments to underline the effectiveness and performance of the proposed method.
引用
收藏
页码:4259 / 4280
页数:22
相关论文
共 50 条