Let K be a nonempty compact convex subset of a uniformly convex Banach space, and   K K T   : a multivalued nonexpansive mapping. We prove that the sequences of Noor iterate converge to a fixed point of T. This generalizes former results proved by Banach convergence of Noor iterates for a multi-valued mapping with a fixed point. We also introduce both of the iterative processes in a new sen...

In this paper we present two Douglas–Rachford inspired iteration schemes which can be applied directly to N-set convex feasibility problems in Hilbert space. Our main results are weak convergence of the methods to a point whose nearest point projections onto each of the N sets coincide. For affine subspaces, convergence is in norm. Initial results from numerical experiments, comparing our metho...

Let $C$ be a nonempty closed convex subset of a real Hilbert space $H$. Let ${S_n}$ and ${T_n}$ be sequences of nonexpansive self-mappings of $C$, where one of them is a strongly nonexpansive sequence. K. Aoyama and Y. Kimura introduced the iteration process $x_{n+1}=beta_nx_n+(1-beta_n)S_n(alpha_nu+(1-alpha_n)T_nx_n)$ for finding the common fixed point of ${S_n}$ and ${T_n}$, where $uin C$ is ...

Effect of external factors on intention–behaviour gap Sedigheh Moghavvemi, Noor Akma Mohd Salleh, Ainin Sulaiman & Masoud Abessi To cite this article: Sedigheh Moghavvemi, Noor Akma Mohd Salleh, Ainin Sulaiman & Masoud Abessi (2015) Effect of external factors on intention–behaviour gap, Behaviour & Information Technology, 34:12, 1171-1185, DOI: 10.1080/0144929X.2015.1055801 To link to this arti...

The single-step one-shot method has proven to be very efficient for PDEconstrained optimization where the partial differential equation (PDE) is solved by an iterative fixed point solver. In this approach, the simulation and optimization tasks are performed simultaneously in a single iteration. If the PDE is unsteady, finding an appropriate fixed point iteration is nontrivial. In this paper, we...