[1] Alakoya T O, Jolaoso L O, Mewomo O T. Modified inertia subgradient extragradient method with self adaptive stepsize for solving monotone variational inequality and fixed point problems. Optimization, 2021, 70(3): 545–574 [2] Alakoya T O, Owolabi A O E, Mewomo O T. An inertial algorithm with a self-adaptive step size for a split equilibrium problem and a fixed point problem of an infinite family of strict pseudo-contractions. J Nonlinear Var Anal, 2021, 5: 803–829 [3] Alakoya T O, Owolabi A O -E, Mewomo O T. Inertial algorithm for solving split mixed equilibrium and fixed point problems for hybrid-type multivalued mappings with no prior knowledge of operator norm. J Nonlinear Convex Anal, 2021, accepted, to appear [4] Alakoya T O, Taiwo A, Mewomo O T, Cho Y J. An iterative algorithm for solving variational inequality, generalized mixed equilibrium, convex minimization and zeros problems for a class of nonexpansive-type mappings. Ann Univ Ferrara Sez VII Sci Mat, 2021, 67(1): 1–31 [5] Attouch H, Cabot A. Convergence rate of a relaxed inertial proximal algorithm for convex minimization. Optimization, 2020, 69(6): 1281–1312 [6] Attouch H, Cabot A. Convergence of a relaxed inertial proximal algorithm for maximally monotone operators. Math Program, 2019: 1–45 [7] Attouch H, Cabot A. Convergence of a relaxed inertial forwardbackward algorithm for structured monotone inclusions. Appl Math Optim, 2019, 80(3): 547–598 [8] Beck A, Teboulle M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J Imaging Sci, 2009, 2(1): 183–202 [9] Byrne C. A unified treatment for some iterative algorithms in signal processing and image reconstruction. Inverse Problems, 2004, 20: 103–120 [10] Ceng L C, Ansari Q H, Yao Y C. Relaxed extragradient methods for finding minimum-norm solutions of the split feasibility problem. Nonlinear Anal, 2012, 75: 2116–2125 [11] Ceng L C, Petrusel A, Qin X, Yao J C. A modified inertial subgradient extragradient method for solving pseudomonotone variational inequalities and common fixed point problems. Fixed Point Theory, 2020, 21(1): 93–108 [12] Censor Y, Elfving T. A multiprojection algorithm using Bregman projections in product space. Numer Algorithms, 1994, 8: 221–239 [13] Censor Y, Gibali A, Reich S. The split variational inequality problem. The Technion-Israel Institute of Technology, Haifa, 2010 [14] Censor Y, Gibali A, Reich S. Algorithms for the split variational inequality problem. Numer Algorithms, 2012, 59: 301–323 [15] Censor Y, Gibali A, Reich S. The subgradient extragradient method for solving variational inequalities in Hilbert space. J Optim Theory Appl, 2011, 148: 318–335 [16] Cholamjiak P, Hieu D V, Cho Y J. Relaxed forward-backward splitting methods for solving variational inclusions and applications. J Sci Comput, 2021, 88 (3): Art 85 [17] Gibali A, Jolaoso L O, Mewomo O T, Taiwo A. Fast and simple Bregman projection methods for solving variational inequalities and related problems in Banach spaces. Results Math, 2020, 75: Art 179 [18] Gibali A, Shehu Y. An efficient iterative method for finding common fixed point and variational inequalities in Hilbert. Optimization, 2019, 68(1): 13–32 [19] Godwin E C, Izuchukwu C, Mewomo O T. An inertial extrapolation method for solving generalized split feasibility problems in real Hilbert spaces. Boll Unione Mat Ital, 2021, 14(2): 379–401 [20] He H, Ling C, Xu H K. A relaxed projection method for split variational inequalities. J Optim Theory Appl, 2015, 166: 213–233 [21] He S, Dong Q L, Tian H. Relaxed projection and contraction methods for solving Lipschitz continuous monotone variational inequalities. Rev R Acad Cienc Exactas F Nat Ser A Mat (RACSAM), 2019, 113: 2763–2781 [22] Gibali A, Shehu Y. An efficient iterative method for finding common fixed point and variational inequalities in Hilbert spaces. Optimization, 2019, 68(1): 13–32 [23] He S, Wu T, Gibali A, Dong Q L. Totally relaxed, self-adaptive algorithm for solving variational inequalities over the intersection of sub-level sets. Optimization, 2018, 67(90): 1487–1504 [24] Hendrickx J M, Olshevsky A. Matrix P-norms are NP-hard to approximate if P ≠ 1, 2, ∞. SIAM J Matrix Anal Appl, 2010, 31: 2802–2812 [25] Hieu D V, Anh P K, Muu L D. Modified hybrid projection methods for finding common solutions to variational inequality problems. Comput Optim Appl, 2017, 66: 75–96 [26] Iutzeler F, Hendrickx J M. A generic online acceleration scheme for optimization algorithms via relaxation and inertia. Optim Methods Softw, 2019, 34(2): 383–405 [27] Izuchukwu C, Ogwo G N, Mewomo O T. An Inertial Method for solving Generalized Split Feasibility Problems over the solution set of Monotone Variational Inclusions. Optimization, 2020, DOI: https://doi.org/10.1080/02331934.2020.1808648 [28] Izuchukwu C, Okeke C C, Mewomo O T. Systems of variational inequality problem and multiple-sets split equality fixed point problem for infinite families of multivalued type-one demicontractive-type mappings. Ukrainian Math J, 2019, 71: 1480–1501 [29] Jolaoso L O, Taiwo A, Alakoya T O, Mewomo O T. Strong convergence theorem for solving pseudomonotone variational inequality problem using projection method in a reflexive Banach space. J Optim Theory Appl, 2020, 185(3): 744–766 [30] Jolaoso L O, Taiwo A, Alakoya T O, Mewomo O T, Dong Q L. A totally relaxed, self-adaptive subgradient extragradient method for variational inequality and fixed point problems in a Banach space. Comput Methods Appl Math, 2021, DOI:https://doi.org/10.1515/cmam-2020-0174 [31] Kesornprom P, Cholamjiak P. Proximal type algorithms involving linesearch and inertial technique for split variational inclusion problem in hilbert spaces with applications. Optimization, 2019, 68: 2365–2391 [32] Kim J K, Salahuddin S, Lim W H. General nonconvex split variational inequality problems. Korean J Math, 2017, 25: 469–481 [33] Khan S H, Alakoya T O, Mewomo O T. Relaxed projection methods with self-adaptive step size for solving variational inequality and fixed point problems for an infinite family of multivalued relatively nonexpansive mappings in Banach spaces. Math Comput Appl, 2020, 25: Art 54 [34] Maingé P E. Approximation methods for common fixed points of nonexpansive mappings in Hilbert spaces. J Math Anal Appl, 2007, 325(1): 469–479 [35] Maingé P E. A viscosity method with no spectral radius requirements for the split common fixed point problem. Eur J Oper Res, 2014, 235: 17–27 [36] Moudafi A. Split monotone variational inclusions. J Optim Theory Appl, 2011, 150: 275–283 [37] Moudafi A, Thakur B S. Solving proximal split feasibility problems without prior knowledge of operator norms. Optim Lett, 2014, 8(7): 2099–2110 [38] Nesterov Y. A method of solving a convex programming problem with convergence rate O(1/k2). Soviet Math Doklady, 1983, 27: 372–376 [39] Ogwo G N, Alakoya T O, Mewomo O T. Iterative algorithm with self-adaptive step size for approximating the common solution of variational inequality and fixed point problems. Optimization, 2021, DOI:https://doi.org/10.1080/02331934.2021.1981897 [40] Ogwo G N, Izuchukwu C, Mewomo O T. Inertial methods for finding minimum-norm solutions of the split variational inequality problem beyond monotonicity. Numer Algorithms, 2021, 88: 1419–1456 [41] Ogwo G N, Izuchukwu C, Shehu Y, Mewomo O T. Convergence of relaxed inertial subgradient extragradient methods for quasimonotone variational inequality problems. J Sci Comput, 2021, DOI:https://doi.org/10.1007/s10915-021-01670-1 [42] Ogwo G N, Izuchukwu C, Mewomo O T. A modified extragradient algorithm for a certain class of split pseudo-monotone variational inequality problem. Numer Algebra Control Optim, 2021, DOI:https://doi.org/10.3934/naco.2021011 [43] Olona M A, Alakoya T O, Owolabi A O-E, Mewomo O T. Inertial shrinking projection algorithm with self-adaptive step size for split generalized equilibrium and fixed point problems for a countable family of nonexpansive multivalued mappings. Demonstr Math, 2021, 54: 47–67 [44] Owolabi A O -E, Alakoya T O, Taiwo A, Mewomo O T. A new inertial-projection algorithm for approximating common solution of variational inequality and fixed point problems of multivalued mappings. Numer Algebra Control Optim, 2021, DOI:https://doi.org/10.3934/naco.2021004 [45] Oyewole O K, Abass H A, Mewomo O T. Strong convergence algorithm for a fixed point constraint split null point problem. Rend Circ Mat Palermo II, 2021, 70(1): 389408 [46] Polyak B T. Some methods of speeding up the convergence of iteration methods. USSR Comput Math and Math Phys, 1964, 4(5): 1–17 [47] Reich S, Tuyen T M. A new algorithm for solving the split common null point problem in Hilbert spaces. Numer Algorithms, 2020, 83: 789–805 [48] Saejung S, Yotkaew P. Approximation of zeros of inverse strongly monotone operators in Banach spaces. Nonlinear Anal: Theory Methods Appl, 2012, 75(2): 742–750 [49] Shehu Y, Cholamjiak P. Iterative method with inertial for variational inequalities in Hilbert spaces. Calcolo, 2019, 56 (1): Art 4 [50] Shehu Y, Li X H, Dong Q L. An efficient projection-type method for monotone variational inequalities in Hilbert spaces. Numer Algorithms, 2020, 84: 365–388 [51] Shehu Y, Ogbuisi F U. An iterative method for solving split monotone variational inclusion and fixed point problems. Rev R Acad Cienc Exactas F Nat Ser A Mat (RACSAM), 2016, 110(2): 503–518 [52] Taiwo A, Alakoya T O, Mewomo O T. Halpern-type iterative process for solving split common fixed point and monotone variational inclusion problem between Banach spaces. Numer Algorithms, 2021, 86(4): 1359–1389 [53] Takahashi W. Nonlinear functional analysis-Fixed Point Theory and its Applications. Yokohama: Yokohama Publishers, 2000 [54] Thong D V, Shehu Y, Iyiola O S. Weak and strong convergence theorems for solving pseudo-monotone variational inequalities with non-Lipschitz mappings. Numer Algorithm, 2019, 84: 795–823 [55] Tian M, Jiang B N. Viscosity approximation methods for a class of generalized split feasibility problems with variational inequalities in Hilbert space. Numer Funct Anal Optim, 2019, 40: 902–923 [56] Tian M, Jiang B N. Weak convergence theorem for a class of split variational inequality problems and applications in Hilbert space. J Inequal Appl, 2017, 2017: Art 123 [57] Tseng P. A modified forward-backward splitting method for maximal monotone mappings. SIAM J Control Optim, 2000, 38: 431–446 [58] Xia Y, Wang J. A general methodology for designing globally convergent optimization neural networks. IEEE Trans Neural Netw, 1998, 9(6): 1331–1343 [59] Xu H K. Iterative methods for the split feasibility problem in infinite dimensional Hilbert spaces. Inverse Problem, 2010, 26: 105018 [60] He S, Xu H K. Uniqueness of supporting hyperplanes and an alternative to solutions of variational inequalities. J Global Optim, 2013, 57(4): 1375–1384 |