We show that various inverse problems in signal recovery can be formulated as the generic
problem of minimizing the sum of two convex functions with certain regularity properties …

The split feasibility problem (SFP)(Censor and Elfving 1994 Numer. Algorithms 8 221–39) is
to find a point x* with the property that x*∊ C and Ax*∊ Q, where C and Q are the nonempty …

The Variational Inequality Problem [6, 52, 118, 119] has been and will continue to be one of
the central problems in nonlinear analysis and is defined as follows: given monotone …

We propose a convergence analysis of accelerated forward-backward splitting methods for
composite function minimization, when the proximity operator is not available in closed form …

In aircraft control, control allocation can be used to distribute the total control effort among
the actuators when the number of actuators exceeds the number of controlled variables. The …

The hybrid steepest descent method is an algorithmic solution to the variational inequality
problem over the fixed point set of nonlinear mapping and applicable to broad range of …

A block-iterative parallel decomposition method is proposed to solve general quadratic
signal recovery problems under convex constraints. The proposed method proceeds by …

The first aim of this paper is to present a useful toolbox of quasi-nonexpansive mappings for
convex optimization from the viewpoint of using their fixed point sets as constraints. Many …

In this article, we propose a modified Korpelevich's method for solving variational
inequalities. Under some mild assumptions, we show that the suggested method converges …

We provide two weakly convergent algorithms for finding a zero of the sum of a maximally
monotone operator, a cocoercive operator, and the normal cone to a closed vector subspace …