Abstract The objective of this article is to solve pseudomonotone variational inequality problems in a real Hilbert space. We introduce an inertial algorithm with a new self-adaptive step size rule, which is based on the projection and contraction method. Only one step projection is used to design the proposed algorithm, and the strong convergence of the iterative sequence is obtained under some appropriate conditions. The main advantage of the algorithm is that the proof of convergence of the algorithm is implemented without the prior knowledge of the Lipschitz constant of cost operator. Numerical experiments are also put forward to support the analysis of the theorem and provide comparisons with related algorithms
In this work we analyze from the numerical viewpoint the class of projection methods for solving pse...
In this paper, we introduce and analyze two new inertial-like algorithms with the Bregman divergence...
The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for ...
In this paper, we introduce two inertial self-adaptive projection and contraction methods for solvin...
The paper deals with an inertial-like algorithm for solving a class of variational inequality proble...
We propose a new projection-type method with inertial extrapolation for solving pseudo-monotone and ...
The main contributions of this paper are the proposition and the convergence analysis of a class of ...
AbstractWe consider and analyze a new projection method for solving pseudomonotone variational inequ...
We propose two new iterative algorithms for solving K-pseudomonotone variational inequality problems...
AbstractIn this paper, we consider and analyze a new class of projection methods for solving pseudom...
AbstractIn this paper, we consider and analyze a new class of projection methods for solving pseudom...
AbstractIn this paper, we propose a new projection method for solving variational inequality problem...
Two new inertial-type extragradient methods are proposed to find a numerical common solution to the ...
AbstractIn this paper, we presented a new projection and contraction method for linear variational i...
In this paper, we introduce an inertial projection-type method with different updating strategies fo...
In this work we analyze from the numerical viewpoint the class of projection methods for solving pse...
In this paper, we introduce and analyze two new inertial-like algorithms with the Bregman divergence...
The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for ...
In this paper, we introduce two inertial self-adaptive projection and contraction methods for solvin...
The paper deals with an inertial-like algorithm for solving a class of variational inequality proble...
We propose a new projection-type method with inertial extrapolation for solving pseudo-monotone and ...
The main contributions of this paper are the proposition and the convergence analysis of a class of ...
AbstractWe consider and analyze a new projection method for solving pseudomonotone variational inequ...
We propose two new iterative algorithms for solving K-pseudomonotone variational inequality problems...
AbstractIn this paper, we consider and analyze a new class of projection methods for solving pseudom...
AbstractIn this paper, we consider and analyze a new class of projection methods for solving pseudom...
AbstractIn this paper, we propose a new projection method for solving variational inequality problem...
Two new inertial-type extragradient methods are proposed to find a numerical common solution to the ...
AbstractIn this paper, we presented a new projection and contraction method for linear variational i...
In this paper, we introduce an inertial projection-type method with different updating strategies fo...
In this work we analyze from the numerical viewpoint the class of projection methods for solving pse...
In this paper, we introduce and analyze two new inertial-like algorithms with the Bregman divergence...
The paper introduces an inertial extragradient subgradient method with self-adaptive step sizes for ...