  In this paper, we propose a catalog of iterative methods for solving the
Split Feasibility Problem in the non-convex setting. We study four different
optimization formulations of the problem, where each model has advantageous in
different settings of the problem. For each model, we study relevant iterative
algorithms, some of which are well-known in this area and some are new. All the
studied methods, including the well-known CQ Algorithm, are proven to have
global convergence guarantees in the non-convex setting under mild conditions
on the problem's data.
