AN INERTIAL TSENG SUBGRADIENT PROJECTION METHOD FOR SOLVING SPLIT FEASIBILITY PROBLEMS IN NON-CONVEX SETTING

被引:0
|
作者
Chen, Jinzuo [1 ]
Liou, Yeong-Cheng [2 ,3 ,4 ]
Yin, Tzu-Chien [5 ]
机构
[1] Lingnan Normal Univ, Sch Math & Stat, Zhanjiang, Peoples R China
[2] Kaohsiung Med Univ, Dept Healthcare Adm & Med Informat, Kaohsiung 807, Taiwan
[3] Kaohsiung Med Univ, Res Ctr Nonlinear Anal & Optimizat, Kaohsiung 807, Taiwan
[4] Kaohsiung Med Univ Hosp, Dept Med Res, Kaohsiung 807, Taiwan
[5] China Med Univ, China Med Univ Hosp, Res Ctr Interneural Comp, Taichung 40402, Taiwan
关键词
Nonconvex split feasibility problems; S-subdifferentiable; S-subgradient projection; Armijo-type line rule; inertial technique; APPROXIMATING SOLUTIONS; CQ ALGORITHM;
D O I
暂无
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this work, we introduce an inertial Tseng subgradient projection method for solving split feasibility problems in finite dimensional spaces. The main advantages of this paper are that the introduced step -size is chosen according to Armijo-type line rule, the construction of iterative algorithm involves inertial technique and the underlying sets are non-convex.
引用
收藏
页码:181 / 189
页数:9
相关论文
共 50 条
  • [31] An inertial extrapolation method for solving generalized split feasibility problems in real hilbert spaces
    Godwin, E. C.
    Izuchukwu, C.
    Mewomo, O. T.
    BOLLETTINO DELLA UNIONE MATEMATICA ITALIANA, 2021, 14 (02): : 379 - 401
  • [32] Exploring the convex transformations for solving non-convex bilinear integer problems
    Harjunkoski, I
    Pörn, R
    Westerlund, T
    COMPUTERS & CHEMICAL ENGINEERING, 1999, 23 : S471 - S474
  • [33] Non-convex feasibility problems and proximal point methods
    Corvellec, JN
    Flåm, SD
    OPTIMIZATION METHODS & SOFTWARE, 2004, 19 (01): : 3 - 14
  • [34] Non-monotonous sequential subgradient projection algorithm for convex feasibility problem
    Ya-zheng Dang
    Jun-ling Sun
    Yan Gao
    Acta Mathematicae Applicatae Sinica, English Series, 2016, 32 : 1101 - 1110
  • [35] Non-monotonous Sequential Subgradient Projection Algorithm for Convex Feasibility Problem
    Ya-zheng DANG
    Jun-ling SUN
    Yan GAO
    ActaMathematicaeApplicataeSinica, 2016, 32 (04) : 1101 - 1110
  • [36] Non-monotonous Sequential Subgradient Projection Algorithm for Convex Feasibility Problem
    Dang, Ya-zheng
    Sun, Jun-ling
    Gao, Yan
    ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES, 2016, 32 (04): : 1101 - 1110
  • [37] Several inertial methods for solving split convex feasibilities and related problems
    Tang, Yan
    Gibali, Aviv
    REVISTA DE LA REAL ACADEMIA DE CIENCIAS EXACTAS FISICAS Y NATURALES SERIE A-MATEMATICAS, 2020, 114 (03)
  • [38] Several inertial methods for solving split convex feasibilities and related problems
    Yan Tang
    Aviv Gibali
    Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales. Serie A. Matemáticas, 2020, 114
  • [39] Two regularized inertial Tseng methods for solving inclusion problems with applications to convex bilevel programming
    Taiwo, Adeolu
    Reich, Simeon
    OPTIMIZATION, 2023,
  • [40] Minibatch stochastic subgradient-based projection algorithms for feasibility problems with convex inequalities
    Ion Necoara
    Angelia Nedić
    Computational Optimization and Applications, 2021, 80 : 121 - 152