1 citations · 1 across the 8 of their papers we have counts for
10 papers
CCOpt: an Open-Source Solver for Large-Scale Mathematical Programs with Complementarity Constraints
Anton Pozharskiy, François Pacaud, Moritz Diehl +1
This paper presents the Julia package CCOpt, built on top of the interior-point solver MadNLP. CCOpt implements a suite of algorithms for Mathematical Programs with Complementarity…
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…
ExaModelsPower.jl: A GPU-Compatible Modeling Library for Nonlinear Power System Optimization
Sanjay Johnson, Dirk Lauinger, Sungho Shin +1
As GPU-accelerated mathematical programming techniques mature, there is growing interest in utilizing them to address the computational challenges of power system optimization. Thi…
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…
Condensed interior-point methods: porting reduced-space approaches on GPU hardware
François Pacaud, Sungho Shin, Michel Schanen +2
The interior-point method (IPM) has become the workhorse method for nonlinear programming. The performance of IPM is directly related to the linear solver employed to factorize the…
A Globally Convergent Distributed Jacobi Scheme for Block-Structured Nonconvex Constrained Optimization Problems
Anirudh Subramanyam, Youngdae Kim, Michel Schanen +2
Motivated by the increasing availability of high-performance parallel computing, we design a distributed parallel algorithm for linearly-coupled block-structured nonconvex constrai…
Decentralized Multistage Optimization of Large-Scale Microgrids under Stochasticity
François Pacaud, Michel de Lara, Jean-Philippe Chancelier +1
Microgrids are recognized as a relevant tool to absorb decentralized renewable energies in the energy mix. However, the sequential handling of multiple stochastic productions and d…