This paper considers the problem of minimizing summation a differentiable function and nonsmooth on Riemannian manifold. In recent years, proximal gradient method its variants have been generalized to setting for solving such problems. Different approaches generalize mapping lead different versions methods. However, their convergence analyses all rely exactly, which is either too expensive or i...

Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 22 April 2020Accepted: 09 July 2021Published online: 21 October 2021Keywordslinear quadratic regulators, optimal control, nonconvex minimization, state feedback, output gradient method, convergenceAMS Subject Headings49N10, 49M37, 90C26, 90C52Publication DataISSN (print):...

in this paper imprecise target models has been proposed to investigate the relation between imprecise data envelopment analysis (idea) and mini-max reference point formulations. through these models, the decision makers' preferences are involved in interactive trade-off analysis procedures in multiple objective linear programming with imprecise data. in addition, the gradient projection type me...

In this paper, a new nonlinear conjugate gradient method is proposed for large-scale unconstrained optimization. The sufficient descent property holds without any line searches. We use some steplength technique which ensures the Zoutendijk condition to be held, this method is proved to be globally convergent. Finally, we improve it, and do further analysis.

T study was motivated primarily by the author’s interest in numerical methods at both a teaching and research level. Much has already been written about “standard” Mathcad 6 and the purpose of this article is to focus on, and use, some of the features of Plus 6 which are not available in the standard version. In particular the use of the programming facility, which comes with Plus 6, is illustr...