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Implementation of a Augmented Lagrangian method

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Percival.jl - An augmented Lagrangian solver

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Percival is an implementation of the augmented Lagrangian solver described in

S. Arreckx, A. Lambe, Martins, J. R. R. A., & Orban, D. (2016).
A Matrix-Free Augmented Lagrangian Algorithm with Application to Large-Scale Structural Design Optimization.
Optimization And Engineering, 17, 359–384. doi:10.1007/s11081-015-9287-9

with internal solver tron from JSOSolvers.jl. To use Percival, you have to pass it an NLPModel.

How to Cite

If you use Percival.jl in your work, please cite using the format given in CITATION.bib.

Install

Use ] to enter pkg> mode of Julia, then

pkg> add https://github.com/JuliaSmoothOptimizers/Percival.jl

Use with JuMP

You can solve an JuMP model m by using NLPModels to convert it.

using NLPModelsJuMP, Percival
nlp = MathOptNLPModel(m)
output = percival(nlp)

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