Monotone Mapping In Hilbert Space Research Articles

Inertial hybrid algorithm for generalized mixed equilibrium problems, zero problems, and fixed points of some nonlinear mappings in the intermediate sense

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.

Strong convergence theorem for common zero points of inverse strongly monotone mappings and common fixed points of generalized demimetric mappings

In this paper, we introduce a new and efficient algorithm for finding a common element of the set of common fixed points of a finite family of generalized demimetric mappings and the set of common zero points of a finite family of inverse strongly monotone mappings in Hilbert spaces. Strong convergence of the proposed algorithm is established under standard and mild conditions in a Hilbert space. As an application, we use our algorithm for solving the common solutions to the variational inequality problem, the common minimization problem, the multiple-set split feasibility problem, the split common fixed point problem and the split common null point problem.

Dual Variable Inertial Accelerated Algorithm for Split System of Null Point Equality Problems

In this paper, we introduce a novel dual variable algorithm accelerated via inertial extrapolation for solving the generalized split inverse problem given as a task of finding the common null point equality of finite family of inverse-strongly monotone mappings in Hilbert spaces. The proposed method uses the dual variable and self-adaptive technique, along with an inertial strategy which aims at getting accelerated convergence. We establish the convergence Theorem of the proposed method under some suitable assumptions. We also apply our result to solve several types of problems. Our results improve and generalize the corresponding several known results announced by many others. Numerical experiments are presented to show the efficiency and comparative performance of the proposed algorithm.

Approximating solutions of the sum of a finite family of maximally monotone mappings in Hilbert spaces

The purpose of this paper is to study the method of approximation for a zero of the sum of a finite family of maximally monotone mappings using viscosity type Douglas–Rachford splitting algorithm and prove some strong convergence theorems of the proposed algorithm under suitable conditions. In addition, we give some applications to the minimization problems. Finally, a numerical example which supports our main result is presented. Our theorems improve and unify most of the results that have been proved for this important class of nonlinear mappings.

A Method of approximation for a zero of the sum of maximally monotone mappings in Hilbert spaces

Our purpose of this study is to construct an algorithm for finding a zero of the sum of two maximally monotone mappings in Hilbert spaces and discus its convergence. The assumption that one of the mappings is α-inverse strongly monotone is dispensed with. In addition, we give some applications to the minimization problem. Our method of proof is of independent interest. Finally, a numerical example which supports our main result is presented. Our theorems improve and unify most of the results that have been proved for this important class of nonlinear mappings.

Viscosity methods for nonexpansive and monotone mappings in Hilbert spaces

Viscosity methods for nonexpansive and monotone mappings in Hilbert spaces

Iterative methods for a class of variational inequalities in Hilbert spaces

In this paper, we introduce implicit and explicit iterative methods for solving a variational inequality problem over the set of zeros for a maximal monotone mapping in Hilbert spaces. As consequence, new modifications of the proximal point method are obtained.

Weak convergence theorem for variational inequality problems with monotone mapping in Hilbert space

We know that variational inequality problem is very important in the nonlinear analysis. The main purpose of this paper is to propose an iterative method for finding an element of the set of solutions of a variational inequality problem with a monotone and Lipschitz continuous mapping in Hilbert space. This iterative method is based on the extragradient method. We get a weak convergence theorem. Using this result, we obtain three weak convergence theorems for the equilibrium problem, the constrained convex minimization problem, and the split feasibility problem.

A New Iterative Method for the Set of Solutions of Equilibrium Problems and of Operator Equations with Inverse-Strongly Monotone Mappings

The purpose of the paper is to present a new iteration method for finding a common element for the set of solutions of equilibrium problems and of operator equations with a finite family ofλi-inverse-strongly monotone mappings in Hilbert spaces.

Iterative method for a finite family of nonexpansive mappings in Hilbert spaces with applications

In this paper, we introduce a new iterative method for finding a common element of the set of solutions of a general system of variational inequalities, the set of solutions of a mixed equilibrium problem and the set of common fixed points of a finite family of nonexpansive mappings in a real Hilbert space. Furthermore, we prove that the studied iterative method converges strongly to a common element of these three sets. Consequently, we apply our main result to the problem of approximating a zero of a finite family of maximal monotone mappings in Hilbert spaces. The theorems presented in this paper, improve and extend the corresponding results of Takahashi and Toyoda [18] and many others.

Strong Convergence Theorems for Maximal and Inverse-Strongly Monotone Mappings in Hilbert Spaces and Applications

In this paper, we prove two strong convergence theorems for finding a common point of the set of zero points of the addition of an inverse-strongly monotone mapping and a maximal monotone operator and the set of zero points of a maximal monotone operator, which is related to an equilibrium problem in a Hilbert space. Such theorems improve and extend the results announced by Y. Liu (Nonlinear Anal. 71:4852–4861, 2009). As applications of the results, we present well-known and new strong convergence theorems which are connected with the variational inequality, the equilibrium problem and the fixed point problem in a Hilbert space.

A new iterative method for finding common solutions of generalized equilibrium problem, fixed point problem of infinite k-strict pseudo-contractive mappings, and quasi-variational inclusion problem

In this article, we introduce a hybrid iterative scheme for finding a common element of the set of solutions for a generalized equilibrium problems, the set of common fixed point for a family of infinite k-strict pseudo-contractive mappings, and the set of solutions of the variational inclusion problem with multi-valued maximal monotone mappings and inverse-strongly monotone mappings in Hilbert space. Under suitable conditions, some strong convergence theorems are proved. Our results extends the recent results in G.L.Acedo and H.K.Xu [2], Zhang, Lee and Chan [8], Takahashi and Toyoda [9], Takahashi and Takahashi [10] and S. S. Chang, H. W. Joseph Lee and C. K. Chan [11], S.Takahashi and W.Takahashi [12]. Moreover, the method of proof adopted in this article is different from those of [4] and [12].

Some Results on an Infinite Family of Nonexpansive Mappings and an Inverse‐Strongly Monotone Mapping in Hilbert Spaces

We study the problem of approximating a common element in the common fixed point set of an infinite family of nonexpansive mappings and in the solution set of a variational inequality involving an inverse‐strongly monotone mapping based on a viscosity approximation iterative method. Strong convergence theorems of common elements are established in the framework of Hilbert spaces.

A general composite iterative method for generalized mixed equilibrium problems, variational inequality problems and optimization problems

In this article, we introduce a new general composite iterative scheme for finding a common element of the set of solutions of a generalized mixed equilibrium problem, the set of fixed points of an infinite family of nonexpansive mappings and the set of solutions of a variational inequality problem for an inverse-strongly monotone mapping in Hilbert spaces. It is shown that the sequence generated by the proposed iterative scheme converges strongly to a common element of the above three sets under suitable control conditions, which solves a certain optimization problem. The results of this article substantially improve, develop, and complement the previous well-known results in this area.2010 Mathematics Subject Classifications: 49J30; 49J40; 47H09; 47H10; 47J20; 47J25; 47J05; 49M05.

A remark on the strong convergence of the over-relaxed proximal point algorithm

This paper illustrates that the conditions and the main proof of two main theorems of Verma [R.U. Verma, The over-relaxed proximal point algorithm based on H-maximal monotonicity design and applications, Computers and Mathematics with Applications 55 (2008) 2673–2679] concerning the strong convergence of the over-relaxed proximal point algorithm for H-maximal monotone mappings in Hilbert spaces are incorrect.

A general iterative method for addressing mixed equilibrium problems and optimization problems

In this paper, we introduce a new general iterative method for finding a common element of the set of solutions of a mixed equilibrium problem (MEP), the set of fixed points of an infinite family of nonexpansive mappings { T n } n = 1 ∞ and the set of solutions of variational inequalities for a ξ -inverse-strongly monotone mapping in Hilbert spaces. Furthermore, we establish the strong convergence theorem for the iterative sequence generated by the proposed iterative algorithm under some suitable conditions, which solves some optimization problems. Our results extend and improve the recent results of Yao et al. [Y. Yao, M.A. Noor, S. Zainab, Y.C. Liou, Mixed equilibrium problems and optimization problems, J. Math. Anal. Appl. 354 (2009) 319–329; Y. Yao, M. A. Noor, Y.C. Liou, On iterative methods for equilibrium problems, Nonlinear Anal. 70 (1) (2009) 479–509] and many others.

A New Iteration Method for Nonexpansive Mappings and Monotone Mappings in Hilbert Spaces

We introduce a new composite iterative scheme by the viscosity approximation method for nonexpansive mappings and monotone mappings in a Hilbert space. It is proved that the sequence generated by the iterative scheme converges strongly to a common point of set of fixed points of nonexpansive mapping and the set of solutions of variational inequality for an inverse-strongly monotone mappings, which is a solution of a certain variational inequality. Our results substantially develop and improve the corresponding results of [Chen et al. 2007 and Iiduka and Takahashi 2005]. Essentially a new approach for finding the fixed points of nonexpansive mappings and solutions of variational inequalities for monotone mappings is provided.

An Algorithm for Finding a Common Solution for a System of Mixed Equilibrium Problem, Quasivariational Inclusion Problem, and Fixed Point Problem of Nonexpansive Semigroup

We introduce a hybrid iterative scheme for finding a common element of the set of solutions for a system of mixed equilibrium problems, the set of common fixed point for nonexpansive semigroup, and the set of solutions of the quasi-variational inclusion problem with multivalued maximal monotone mappings and inverse-strongly monotone mappings in Hilbert space. Under suitable conditions, some strong convergence theorems are proved. Our results extend some recent results announced by some authors.

Convergence of Paths for Perturbed Maximal Monotone Mappings in Hilbert Spaces

Let be a Hilbert space and a nonempty closed convex subset of . Let be a maximal monotone mapping and a bounded demicontinuous strong pseudocontraction. Let be the unique solution to the equation . Then is bounded if and only if converges strongly to a zero point of A as which is the unique solution in , where denotes the zero set of , to the following variational inequality , for all .

Regularization Inertial Proximal Point Algorithm for Monotone Hemicontinuous Mapping and Inverse Strongly Monotone Mappings in Hilbert Spaces

The purpose of this paper is to present a regularization variant of the inertial proximal point algorithm for finding a common element of the set of solutions for a variational inequality problem involving a hemicontinuous monotone mapping and for a finite family of -inverse strongly monotone mappings from a closed convex subset of a Hilbert space into .