1 citations · 1 across the 8 of their papers we have counts for
5 papers · 2 filters
An Augmented Lagrangian Method on GPU for Security-Constrained AC Optimal Power Flow
François Pacaud, Armin Nurkanović, Anton Pozharskiy +2
We present a new algorithm for solving large-scale security-constrained optimal power flow in polar form (AC-SCOPF). The method builds on Nonlinearly Constrained augmented Lagrangi…
MadNCL: A GPU Implementation of Algorithm NCL for Large-Scale, Degenerate Nonlinear Programs
Alexis Montoison, François Pacaud, Michael Saunders +2
We present a GPU implementation of Algorithm NCL, an augmented Lagrangian method for solving large-scale and degenerate nonlinear programs. Although interior-point methods and sequ…
GPU Implementation of Second-Order Linear and Nonlinear Programming Solvers
Alexis Montoison, François Pacaud, Sungho Shin +1
In recent years, GPU-accelerated optimization solvers based on second-order methods (e.g., interior-point methods) have gained momentum with the advent of mature and efficient GPU-…
Sensitivity analysis for parametric nonlinear programming: A tutorial
François Pacaud
This tutorial provides an overview of the current state-of-the-art in the sensitivity analysis for nonlinear programming. Building upon the fundamental work of Fiacco, it derives t…
Recovering sparse DFT from missing signals via interior point method on GPU
Wei Kuang, Alexis Montoison, Vishwas Rao +2
We propose a method to recover the sparse discrete Fourier transform (DFT) of a signal that is both noisy and potentially incomplete, with missing values. The problem is formulated…