A stochastic computing procedure to solve the dynamics of prevention in HIV system

M Umar, F Amin, Q Al-Mdallal, MR Ali - Biomedical Signal Processing and …, 2022 - Elsevier
The motive of this work is to find the numerical simulations of a dynamical HIV model along
with the effects of prevention, ie, HIPV nonlinear mathematical system. An advance …

A reverse augmented constraint preconditioner for Lagrange multiplier methods in contact mechanics

A Franceschini, M Ferronato, M Frigo… - Computer Methods in …, 2022 - Elsevier
Frictional contact is one of the most challenging problems in computational mechanics.
Typically, it is a tough non-linear problem often requiring several Newton iterations to …

A new preconditioning approach for an interior point‐proximal method of multipliers for linear and convex quadratic programming

L Bergamaschi, J Gondzio, Á Martínez… - … Linear Algebra with …, 2021 - Wiley Online Library
In this article, we address the efficient numerical solution of linear and quadratic
programming problems, often of large scale. With this aim, we devise an infeasible interior …

Gudermannian neural networks to investigate the liénard differential model

B Wang, Y Wang, JF Gómez-Aguilar, Z Sabir… - Fractals, 2022 - World Scientific
The aim of this study is to present the numerical solutions of the Liénard nonlinear model by
designing the structure of the computational Gudermannian neural networks (GNNs) along …

General-purpose preconditioning for regularized interior point methods

J Gondzio, S Pougkakiotis, JW Pearson - Computational Optimization and …, 2022 - Springer
In this paper we present general-purpose preconditioners for regularized augmented
systems, and their corresponding normal equations, arising from optimization problems. We …

A zeroth-order proximal stochastic gradient method for weakly convex stochastic optimization

S Pougkakiotis, D Kalogerias - SIAM Journal on Scientific Computing, 2023 - SIAM
In this paper we analyze a zeroth-order proximal stochastic gradient method suitable for the
minimization of weakly convex stochastic optimization problems. We consider nonsmooth …

Improved penalty algorithm for mixed integer PDE constrained optimization problems

D Garmatter, M Porcelli, F Rinaldi, M Stoll - Computers & Mathematics with …, 2022 - Elsevier
Optimal control problems including partial differential equation (PDE) as well as integer
constraints merge the combinatorial difficulties of integer programming and the challenges …

An efficient active-set method with applications to sparse approximations and risk minimization

S Pougkakiotis, J Gondzio, D Kalogerias - arXiv preprint arXiv:2405.04172, 2024 - arxiv.org
In this paper we present an efficient active-set method for the solution of convex quadratic
programming problems with general piecewise-linear terms in the objective, with …

Block preconditioners for linear systems in interior point methods for convex constrained optimization

G Zilli, L Bergamaschi - ANNALI DELL'UNIVERSITA'DI FERRARA, 2022 - Springer
In this paper, we address the preconditioned iterative solution of the saddle-point linear
systems arising from the (regularized) Interior Point method applied to linear and quadratic …

On the implementation of a quasi-Newton interior-point method for PDE-constrained optimization using finite element discretizations

CG Petra, M Salazar De Troya, N Petra… - Optimization Methods …, 2023 - Taylor & Francis
We present a quasi-Newton interior-point method appropriate for optimization problems with
pointwise inequality constraints in Hilbert function spaces. Among others, our methodology …