On the behavior of subgradient projections methods for convex feasibility problems in Euclidean spaces
Dan Butnariu (dbutnarumath.haifa.ac.il)
Abstract: 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.
Keywords: Subgradient projections, convex feasibility, steering parameters, strategical relaxation.
Category 1: Convex and Nonsmooth Optimization (Convex Optimization )
Citation: Technical report, April 22, 2007. Revised: December 31, 2007. Revised: February 5, 2008. SIAM Journal on Optimization, Vol. 19 (2008), pp.786-807.
Entry Submitted: 04/17/2008
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