Two novel self-adaptive projection algorithms for split feasibility problems with multiple output sets
摘要
We introduce two novel iterative algorithms to solve a split convex feasibility problem with multiple output sets in real Hilbert spaces. These algorithms are based on the projection method for the associated variational inequalities and incorporate self-updating step sizes that do not require knowledge of the norms of the shift operators. The convergence of the sequences generated by the proposed algorithms is proven. Some numerical experiments are given to evaluate the performance of our proposed algorithms.