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In this paper, we use the simultaneous and cyclic subgradient projection methods with perturbations and apply them to linear and nonlinear optimization problems arising naturally in IMRT. The numerical results illustrate the mechanism of the perturbations and demonstrate that they lead to a significantly faster termination of the algorithm, especially when the problem is ill-conditioned.

The Douglas-Rachford (DR) algorithm is an iterative procedure that uses sequential reflections onto convex sets and which has become popular for convex feasibility problems. In this paper we propose a structural generalization that allows to use $r$-sets-DR operators in a cyclic fashion. We prove convergence and present numerical illustrations of the potential advantage of such operators with $r>2$ over the classical $2$-sets-DR operators in a cyclic algorithm., Accepted for publication in Optimization Methods and Software (OMS) July 17, 2018

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In this paper we study the convergence of continuous Newton method for solving nonlinear equations with holomorphic mappings in complex Banach spaces. Our contribution is based on a recent progress in the geometric theory of spirallike functions. We prove convergence theorems and illustrate them by numerical simulations.