ON THE BEHAVIOR OF SUBGRADIENT PROJECTIONSMETHODS FOR CONVEX FEASIBILITY PROBLEMS INEUCLIDEAN SPACES

摘要

We study some methods of subgradient projections for solving a convex feasibilityproblem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent caseand propose a strategy that controls the relaxation parameters in a specific self-adapting manner.This strategy leaves enough user flexibility but gives a mathematical guarantee for the algorithm'sbehavior in the inconsistent case. We present the numerical results of computational experimentsthat illustrate the computational advantage of the new method.