Solving Equilibrium Problems Research Articles

Gradient projection-type algorithms for solving equilibrium problems and its applications

In this paper, we study strongly pseudo-monotone equilibrium problems in real Hilbert and introduce two simple subgradient-type methods for solving it. The advantages of our schemes are the simplicity of their algorithmic structure which consists of only one projection onto the feasible set and there is no need to solve any strongly convex programming problem, which is often used in related methods in the literature. Under mild and standard assumptions, strong convergence theorems of the proposed algorithms are established. We test and compare the performances of our schemes with some related methods in the literature for solving the Nash–Cournot oligopolistic equilibrium model.

Explicit iterative algorithms for solving equilibrium problems

The paper introduces two new extragradient algorithms for solving a pseudomonotone equilibrium problem with a Lipschitz-type condition recently presented by Mastroeni in auxiliary problem principle. The algorithm uses variable stepsizes which are updated at each iteration and based on some previous iterates. The advantage of the algorithms is that they are done without the prior knowledge of Lipschitz-type constants and also without any linesearch procedure. The convergence of the algorithms is established under mild assumptions. In the case where the equilibrium bifunction is strongly pseudomonotone, the R-linear rate of convergence of the new algorithms is formulated. Several of fundamental experiments are provided to illustrate the numerical behavior of the algorithms and also to compare with others.

On a Bregman regularized proximal point method for solving equilibrium problems

In this paper, we propose a Bregman regularized proximal point method for solving monotone equilibrium problems. Existence and uniqueness results as well as convergence of the sequence to a solution of an equilibrium problem is analyzed. We assume a coercivity condition on the Bregman function weaker than the one considered in the literature on equilibrium problems with Bregman regularization. Numerical experiments illustrate the efficiency of the method.

An iterative algorithm for solving equilibrium problems, variational inequalities and fixed point problems of multivalued quasi-nonexpansive mappings

An iterative algorithm for solving equilibrium problems, variational inequalities and fixed point problems of multivalued quasi-nonexpansive mappings

Self-adaptive ergodic algorithm for equilibrium problems over the fixed point set

ABSTRACTWe introduce a new ergodic algorithm for solving equilibrium problems over the fixed point set of a nonexpansive mapping. In contrast to the existing one in Kim [The Bruck's ergodic iteration method for the Ky Fan inequality over the fixed point set. Int. J. Comput. Math. 94 (2017), pp. 2466–2480], our algorithm uses self-adaptive step sizes. Thanks to that, the proposed algorithm converges under milder conditions. Moreover, at each step of our algorithm, instead of solving strongly convex problems, we only have to compute a subgradient of a convex function. Hence, our algorithm has lower computational cost.

A splitting algorithm for finding fixed points of nonexpansive mappings and solving equilibrium problems

We consider the problem of finding a fixed point of a nonexpansive mapping, which is also a solution of a pseudo-monotone equilibrium problem, where the bifunction in the equilibrium problem is the sum of two ones. We propose a splitting algorithm combining the gradient method for equilibrium problem and the Mann iteration scheme for fixed points of nonexpansive mappings. At each iteration of the algorithm, two strongly convex subprograms are required to solve separately, one for each of the component bifunctions. Our main result states that, under paramonotonicity property of the given bifunction, the algorithm converges to a solution without any Lipschitz-type condition as well as Holder continuity of the bifunctions involved.

Modified extragradient algorithms for solving equilibrium problems

ABSTRACTIn this paper, we introduce some new algorithms for solving the equilibrium problem in a Hilbert space which are constructed around the proximal-like mapping and inertial effect. Also, some convergence theorems of the algorithms are established under mild conditions. Finally, several experiments are performed to show the computational efficiency and the advantage of the proposed algorithm over other well-known algorithms.

Computational Errors of the Extragradient Method for Equilibrium Problems

Our aim in this paper is to study variants and computational errors of the extragradient method for solving equilibrium problems. First, we consider convergence of the method when domains in the auxiliary subproblems of the extragradient algorithm are replaced by outer and inner approximation polyhedra. Then, computational errors are showed under the asymptotic optimality condition, but the bifunction must satisfy certain Lipschitz-type continuous conditions. Next, by using Armijo-type linesearch techniques commonly used in variational inequalities, we obtain an approximation linesearch algorithm without Lipschitz continuity. Convergence analysis of the algorithms is considered under mild conditions on the iterative parameters.

A splitting algorithm for equilibrium problem given by the difference of two bifunctions

In this paper, we introduce a splitting algorithm for solving equilibrium problems given by the difference of two bifunctions in a real Hilbert space. Under suitable assumptions on component bifunctions, we prove strong convergence of the proposed algorithm. In contrast to most existing projection-type methods for equilibrium problems, our algorithm does not require any convexity or monotonicity conditions on the resulting bifunction. Some numerical experiments and comparisons are given to illustrate the efficiency of the proposed algorithm.

A strong convergence theorem for split mixed equilibrium and fixed point problems for nonexpansive mappings

The aim of this work is twofold; first, to give an extension to split mixed equilibrium problem. Secondly, we suggest and analyze an iterative method based on Mann iterative method and Halpern iterative method to find a common solution of split mixed equilibrium problem and fixed point problem for a nonexpansive mapping in the framework of real Hilbert spaces. Further, under some mild conditions, strong convergence theorem is obtained by the sequences generated by the proposed iterative method, which solves the variational inequality problem. Furthermore, we derived some consequences from our main result and provide some numerical experiments. Our results can be viewed as significant extension and generalization of the previously known results for solving equilibrium problems.

A strong convergence theorem for Bregman quasi-noexpansive mappings with applications

In this paper we propose a new iterative algorithm for finding a common fixed point of an infinitely countable family of Bregman quasi-nonexpansive mappings in reflexive Banach spaces. We give some applications of our algorithm to solving equilibrium problems, convex feasibility problems, variational inequalities of monotone operators and finding zeros of maximal monotone operators.

Modified basic projection methods for a class of equilibrium problems

Projection methods are a popular class of methods for solving equilibrium problems. In this paper, we propose approximate one projection methods for solving a class of equilibrium problems, where the cost bifunctions are paramonotone, the feasible sets are defined by a continuous convex function inequality and not necessarily differentiable in the Euclidean space \(\mathcal R^{s}\). At each main iteration step in our algorithms, the usual projections onto the feasible set are replaced by computing inexact subgradients and one projection onto the intersection of two halfspaces containing the solution set of the equilibrium problems. Then, by choosing suitable parameters, we prove convergence of the whole generated sequence to a solution of the problems, under only the assumptions of continuity and paramonotonicity of the bifunctions. Finally, we present some computational examples to illustrate the assumptions of the proposed algorithms.

The Glowinski–Le Tallec splitting method revisited in the framework of equilibrium problems in Hilbert spaces

In this paper, we introduce a new approach for solving equilibrium problems in Hilbert spaces. First, we transform the equilibrium problem into the problem of finding a zero of a sum of two maximal monotone operators. Then, we solve the resulting problem using the Glowinski–Le Tallec splitting method and we obtain a linear rate of convergence depending on two parameters. In particular, we enlarge significantly the range of these parameters given rise to the convergence. We prove that the sequence generated by the new method converges to a global solution of the considered equilibrium problem. Finally, numerical tests are displayed to show the efficiency of the new approach.

A new shrinking gradient-like projection method for equilibrium problems

The paper proposes a new shrinking gradient-like projection method for solving equilibrium problems. The algorithm combines the generalized gradient-like projection method with the monotone hybrid method. Only one optimization program is solved onto the feasible set at each iteration in our algorithm without any extra-step dealing with the feasible set. The absence of an optimization problem in the algorithm is explained by constructing slightly different cutting-halfspace in the monotone hybrid method. Theorem of strong convergence is established under standard assumptions imposed on equilibrium bifunctions. An application of the proposed algorithm to multivalued variational inequality problems (MVIP) is presented. Finally, another algorithm is introduced for MVIPs in which we only use a value of main operator at the current approximation to construct the next approximation. Some preliminary numerical experiments are implemented to illustrate the convergence and computational performance of our algorithms over others.

Extragradient Methods for Solving Equilibrium Problems, Variational Inequalities, and Fixed Point Problems

ABSTRACTIn this paper, we propose the new extragradient algorithms for an α-inverse-strongly monotone operator and a relatively nonexpansive mapping in Banach spaces. We prove convergence theorems by this methods under suitable conditions. Applying our algorithms, we find a zero paint of maximal monotone operators. Using FMINCON optimization toolbox in MATLAB, we give an example to illustrate the usability of our results.

An Inexact Proximal Method with Proximal Distances for Quasimonotone Equilibrium Problems

In this paper, we propose an inexact proximal point method to solve equilibrium problems using proximal distances and the diagonal subdifferential. Under some natural assumptions on the problem and the quasimonotonicity condition on the bifunction, we prove that the sequence generated by the method converges to a solution point of the problem.

Applications of the KKM Property to Coincidence Theorems, Equilibrium Problems, Minimax Inequalities and Variational Relation Problems

ABSTRACTIn this paper, we establish coincidence-like results in the case when the values of the correspondences are not convex. To do this, we define new type of correspondences, namely, properly quasi-convex-like correspondences. Further, we apply the obtained theorems to solve equilibrium problems and to establish a minimax inequality. In the last part of the paper, we study the existence of solutions for generalized vector variational relation problems. Our analysis is based on the applications of the KKM principle. We establish existence theorems involving new hypothesis and we improve the results of some recent papers.

An extension of hybrid method without extrapolation step to equilibrium problems

In this paper, we introduce a new hybrid algorithm for solving equilibrium problems. The algorithm combines the generalized gradient-like projection method and the hybrid (outer approximation) method. In this algorithm, only one optimization program is solved at each iteration without any extra-step dealing with the feasible set like as in the hybrid extragradient method and the hybrid Armijo linesearch method. A specially constructed half-space in the hybrid method is the reason for the absence of an optimization program in the proposed algorithm. The strongly convergent theorem is established and several numerical experiments are implemented to illustrate the convergence of the algorithm and compare it with others.

Two new splitting algorithms for equilibrium problems

In this paper, sequential and parallel splitting algorithms are proposed for solving equilibrium problems given by a sum of two functions. The convergence of the sequences generated by the proposed methods is guaranteed by assuming the Holder continuity of each function. Some preliminary numerical experiences and comparisons are also reported.

A New Algorithm for Finding Fixed Points of Bregman Quasi-Nonexpansive Mappings and Zeros of Maximal Monotone Operators by Using Products of Resolvents

In this paper, we propose a new iterative algorithm for finding a common fixed point of an infinitely countable family of Bregman quasi-nonexpansive mappings and a common zero of finitely many maximal monotone operators in reflexive Banach spaces. An application of our algorithm for solving equilibrium problems will also be exhibited.