8 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…
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-…
A General and Streamlined Differentiable Optimization Framework
Andrew W. Rosemberg, Joaquim Dias Garcia, François Pacaud +5
Differentiating through constrained optimization problems is increasingly central to learning, control, and large-scale decision-making systems, yet practical integration remains c…
An Augmented Lagrangian Method on GPU for Security-Constrained AC Optimal Power Flow
François Pacaud, Armin NurkanoviÄ, 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…