“…Let S be nonempty, bounded, closed, and convex subset of a real Hilbert space H. Let B π βΆ S β H be a finite family of π π -hemicontinuous and relaxed π π β π π monotone maps, π π βΆ S Γ S β R be a finite family of bifunctions satisfying conditions (F1)-(F4) and g π βΆ S β R be a finite family of proper, convex, and lower semicontinuous functions. Let T i βΆ S β S be a family of equally continuous maps that satisfy (7) and A i βΆ S β H be a family of maps defined in (10) with…”
Section: Approximating a Common Solution Of Variational Inequality Pr...mentioning
confidence: 99%
“…Also, T is nonexpansive with 0 β F(T) and consequently satisfies (7) with V n , r, k n = 0, and T n = T βn β N. Also, A satisfies (10) with π = 1 3 and 0 β A β1 (0). The performance of our proposed Algorithm ( 36) is compared with that of the algorithms of Husain and Asad [23] and Harbau and Ahmad [51] with T 1 = T 2 = T, which are as follows, respectively,…”
In this work, we establish the closedness and convexity of the set of fixed points of equally continuous and asymptotically demicontractive mapping in the intermediate sense. We proposed an inertial hybrid projection technique for determining an approximate common solution to three significant problems. The first is the system of generalized mixed equilibrium problems with relaxed
monotone mappings, the second is the problem of fixed points of a countable family of equally continuous and asymptotically demicontractive mappings in the intermediate sense, and the third is of determining a point in a null space of a countable family of inverse strongly monotone mappings in Hilbert space. Based on these problems, we formulate a theorem and establish its strong convergence to their common solution. Additionally, we studied the applications of our algorithm to variational inequality problems and convex optimization problems. Finally, we numerically demonstrate the efficiency and robustness of our scheme. Several results available in the literature can be obtained as special cases of our result.
“…Let S be nonempty, bounded, closed, and convex subset of a real Hilbert space H. Let B π βΆ S β H be a finite family of π π -hemicontinuous and relaxed π π β π π monotone maps, π π βΆ S Γ S β R be a finite family of bifunctions satisfying conditions (F1)-(F4) and g π βΆ S β R be a finite family of proper, convex, and lower semicontinuous functions. Let T i βΆ S β S be a family of equally continuous maps that satisfy (7) and A i βΆ S β H be a family of maps defined in (10) with…”
Section: Approximating a Common Solution Of Variational Inequality Pr...mentioning
confidence: 99%
“…Also, T is nonexpansive with 0 β F(T) and consequently satisfies (7) with V n , r, k n = 0, and T n = T βn β N. Also, A satisfies (10) with π = 1 3 and 0 β A β1 (0). The performance of our proposed Algorithm ( 36) is compared with that of the algorithms of Husain and Asad [23] and Harbau and Ahmad [51] with T 1 = T 2 = T, which are as follows, respectively,…”
In this work, we establish the closedness and convexity of the set of fixed points of equally continuous and asymptotically demicontractive mapping in the intermediate sense. We proposed an inertial hybrid projection technique for determining an approximate common solution to three significant problems. The first is the system of generalized mixed equilibrium problems with relaxed
monotone mappings, the second is the problem of fixed points of a countable family of equally continuous and asymptotically demicontractive mappings in the intermediate sense, and the third is of determining a point in a null space of a countable family of inverse strongly monotone mappings in Hilbert space. Based on these problems, we formulate a theorem and establish its strong convergence to their common solution. Additionally, we studied the applications of our algorithm to variational inequality problems and convex optimization problems. Finally, we numerically demonstrate the efficiency and robustness of our scheme. Several results available in the literature can be obtained as special cases of our result.
“…. , 10 and b (10) n = 5 9 β’ 1 β n + 100 , c (10) n = 1 ( β n + 100) 2 , a (10) n = 1b (10) n + c (10) n = 9n + 1795 β n + 89,491 9( β n + 100) 2 ,…”
Section: Corollary 34 Let B Be a Nonempty Closed Convex Subset Of X mentioning
confidence: 99%
“…Application of strictly hemicontractive-type mapping was initiated by Chidume and Osilike [4] for improving the consequence of Chidume [5]. After Chidume and Osilike [4], several researchers studied strictly hemicontractive-type mapping in many directions; see for instance [1][2][3][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] and the references cited therein. Among the articles cited in [1][2][3][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21], Hussain et al [1] studied Lipschitz strictly hemicontractive-type mapping in arbitrary Banach spaces to extend and improve the equivalent consequences of the monographs [4,5,[12][13][14]…”
In this paper, we introduce and study a modified multi-step Noor iterative procedure with errors for two Lipschitz strictly hemicontractive-type mappings in arbitrary Banach spaces and constitute its convergence and stability. The obtained results in this paper generalize and extend the corresponding result of Hussain et al. (Fixed Point Theory Appl. 2012:160, 2012) and some analogous results of several authors in the literature. Finally, a numerical example is included to illustrate our analytical results and to display the efficiency of our proposed novel iterative procedure with errors.
We introduce a new three step iterative scheme with errors to approximate the unique common fixed point of a family of three strongly pseudocontractive (accretive) mappings on Banach spaces. Our results are generalizations and improvements of results obtained by several authors in literature. In particular, they generalize and improve the results of Mogbademu and Olaleru [A.
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