On The Behavior of Subgradient Projections Methods for Convex Feasibility Problems in Euclidean Spaces.
We study some methods of subgradient projections for solving a convex feasibility problem with general (not necessarily hyperplanes or half-spaces) convex sets in the inconsistent case and 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's behavior in the inconsistent case. We present numerical results of computational experiments that illustrate the computational advantage of the new method.
Butnariu
Dan
D
Department of Mathematics, University of Haifa Mt. Carmel, Haifa 31905, Israel ( dbutnaru@math.haifa.ac.il , yair@math.haifa.ac.il ).
Censor
Yair
Y
Gurfil
Pini
P
Hadar
Ethan
E