Weak and strong convergence theorems for variational inequality problems

DV Thong, DV Hieu - Numerical Algorithms, 2018 - Springer
Numerical Algorithms, 2018Springer
In this paper, we study the weak and strong convergence of two algorithms for solving
Lipschitz continuous and monotone variational inequalities. The algorithms are inspired by
Tseng's extragradient method and the viscosity method with Armijo-like step size rule. The
main advantages of our algorithms are that the construction of solution approximations and
the proof of convergence of the algorithms are performed without the prior knowledge of the
Lipschitz constant of cost operators. Finally, we provide numerical experiments to show the …
Abstract
In this paper, we study the weak and strong convergence of two algorithms for solving Lipschitz continuous and monotone variational inequalities. The algorithms are inspired by Tseng’s extragradient method and the viscosity method with Armijo-like step size rule. The main advantages of our algorithms are that the construction of solution approximations and the proof of convergence of the algorithms are performed without the prior knowledge of the Lipschitz constant of cost operators. Finally, we provide numerical experiments to show the efficiency and advantage of the proposed algorithms.
Springer
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