
doi: 10.3934/jimo.2020123
<p style='text-indent:20px;'>The purpose of this paper is to introduce a new inertial iterative method for solving split variational inclusion problems in real Hilbert spaces. We prove that the generated sequence converges weakly to the solution of the considered problem under some mild conditions. The major contributions of our results are: (ⅰ) to increase the rate of convergence of the method for solving split variational inclusion problem through the inertial extrapolation step, (ⅱ) to relax the choice of the inertial factor and show the inertial factor can be chosen greater than 1/3 unlike what is previously known before for inertial proximal point method in the literature (ⅲ) to show the numerical efficiency and superiority of our proposed method through some test example.</p>
Numerical optimization and variational techniques, Convex programming, Numerical methods based on nonlinear programming, inertial method, Hilbert space, weak convergence, resolvent operator, maximal monotone operator, Set-valued and variational analysis
Numerical optimization and variational techniques, Convex programming, Numerical methods based on nonlinear programming, inertial method, Hilbert space, weak convergence, resolvent operator, maximal monotone operator, Set-valued and variational analysis
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