A Relaxed Proximal Point Algorithm with Double-Inertial Effects for Nonconvex Equilibrium Problems

We present a relaxed proximal point method with double inertial effects to approximate a solution to a non-convex equilibrium problem. We establish the global convergence of the iterative sequence generated by our algorithm. Some known results are recovered as special cases of our findings. An application to mixed variational inequality problems is given. A numerical test is provided to support the theoretical results, and we show that our proposed algorithm outperforms some existing methods in certain cases.