Inertial Subgradient Extragradient Methods for Solving Variational Inequality Problems and Fixed Point Problems
Copyright policy )Inertial Subgradient Extragradient Methods for Solving Variational Inequality Problems and Fixed Point Problems
We propose two new iterative algorithms for solving K-pseudomonotone variational inequality problems in the framework of real Hilbert spaces. These newly proposed methods are obtained by combining the viscosity approximation algorithm, the Picard Mann algorithm and the inertial subgradient extragradient method. We establish some strong convergence theorems for our newly developed methods under certain restriction. Our results extend and improve several recently announced results. Furthermore, we give several numerical experiments to show that our proposed algorithms performs better in comparison with several existing methods.
Variational inequality problems, nertial iterative algorithms, Economics, Fixed-Point Problems, variational inequality problems, Fixed Point Theorems in Metric Spaces, Interior-Point Methods, Computer security, Strong convergence, Inertial iterative algorithms, Hilbert spaces, Subgradient method, Variational inequality, Numerical Analysis, Numerical Optimization Techniques, K-pseudomonotone, Equilibrium Problems, Physics, Mathematical optimization, Hilbert space, Iterative Algorithms for Nonlinear Operators and Optimization, Iterative method, Algorithm, Computational Theory and Mathematics, Physical Sciences, Convergence (economics), Geometry, Mathematical analysis, Quantum mechanics, Point (geometry), QA1-939, FOS: Mathematics, Iterative Algorithms, Weak convergence, Economic growth, Fixed point, Applied mathematics, Computer science, strong convergence, K-pseudomonotone; inertial iterative algorithms; variational inequality problems; Hilbert spaces; strong convergence, Computer Science, Geometry and Topology, Inertial frame of reference, inertial iterative algorithms, Mathematics, Mixed-Integer Nonlinear Programs, Asset (computer security)
Variational inequality problems, nertial iterative algorithms, Economics, Fixed-Point Problems, variational inequality problems, Fixed Point Theorems in Metric Spaces, Interior-Point Methods, Computer security, Strong convergence, Inertial iterative algorithms, Hilbert spaces, Subgradient method, Variational inequality, Numerical Analysis, Numerical Optimization Techniques, K-pseudomonotone, Equilibrium Problems, Physics, Mathematical optimization, Hilbert space, Iterative Algorithms for Nonlinear Operators and Optimization, Iterative method, Algorithm, Computational Theory and Mathematics, Physical Sciences, Convergence (economics), Geometry, Mathematical analysis, Quantum mechanics, Point (geometry), QA1-939, FOS: Mathematics, Iterative Algorithms, Weak convergence, Economic growth, Fixed point, Applied mathematics, Computer science, strong convergence, K-pseudomonotone; inertial iterative algorithms; variational inequality problems; Hilbert spaces; strong convergence, Computer Science, Geometry and Topology, Inertial frame of reference, inertial iterative algorithms, Mathematics, Mixed-Integer Nonlinear Programs, Asset (computer security)
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