A proximal forward–reflected method with momentum effects for solving mixed variational inequality problems
Chidi Elijah Nwakpa, Austine Efut Ofem, Chinedu Izuchukwu, Chibueze Christian Okeke · Optimization · 2025
We study in this paper a proximal forward–reflected method for solving a non-convex mixed variational inequality problem in a real finite space. This method incorporates the momentum terms to obtain the global convergence and the non-asymptotic convergence rate O(1/n) of the generated sequence under some weaker assumptions on the non-convex scalar function h and the Lipschitz operator T. Finally, we present some numerical examples that allow us to advantageously relate our proposed method to other already existing methods.