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New inertial proximal algorithms for solving multivalued variational inequalities
New inertial proximal algorithms for solving multivalued variational inequalities
Phạm Ngọc Anh
This paper presents two new algorithms for solving multivalued variational inequality problems
in a real Hilbert space. By combining the nonexpansiveness of proximal operators associated with
the proper lower semicontinuous convex function of the problems and inertial techniques, we demonstrate
the weak convergence of the iteration sequences generated by our first algorithm under monotone
and Lipschitz continuous assumptions of the cost mappings. Next, we use Mann iteration technique to
obtain the second algorithm and show its strong convergence. Finally, we give some numerical results
for two proposed algorithms and comparison with some other known algorithms.