Accelerated inertial subgradient extragradient algorithms with non-monotonic step sizes for equilibrium problems and fixed point problems

. This paper introduces several new accelerated subgradient extragradient methods with inertial effects for approximating a solution of a pseudomonotone equilibrium problem and a fixed point problem involving a quasi-nonexpansive mapping or a demicontractive mapping in real Hilbert spaces. The proposed algorithms use an adaptive non-monotonic step size criterion that does not include any Armijo line search process. Strong convergence theorems of the suggested iterative algorithms are established without the prior knowledge of the Lipschitz constants of the bifunction. Moreover, R -linear convergence is guaranteed under the assumption that the bifunction satisfies strong pseudomonotonicity. Applications to variational inequality problems are also considered. Finally, some numerical examples and applications, which demonstrate the advantages and efficiency of the proposed algorithms, are given.