https://github.com/abelsiqueira/auglag.jl
Implementation of a Augmented Lagrangian method
Science Score: 13.0%
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Low similarity (8.6%) to scientific vocabulary
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Implementation of a Augmented Lagrangian method
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- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 3
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Fork of JuliaSmoothOptimizers/Percival.jl
Created almost 7 years ago
· Last pushed about 5 years ago
https://github.com/abelsiqueira/AugLag.jl/blob/master/
# Percival.jl - An augmented Lagrangian solver
[](https://github.com/JuliaSmoothOptimizers/Percival.jl/actions)
[](https://codecov.io/github/JuliaSmoothOptimizers/Percival.jl?branch=master)
[](https://JuliaSmoothOptimizers.github.io/Percival.jl/latest)
[](https://JuliaSmoothOptimizers.github.io/Percival.jl/dev)
[](https://doi.org/10.5281/zenodo.3969045)
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, 359384. doi:10.1007/s11081-015-9287-9
with internal solver `tron` from [JSOSolvers.jl](https://github.com/JuliaSmoothOptimizers/JSOSolvers.jl).
To use Percival, you have to pass it an [NLPModel](https://github.com/JuliaSmoothOptimizers/NLPModels.jl).
## How to Cite
If you use Percival.jl in your work, please cite using the format given in [CITATION.bib](CITATION.bib).
## Install
Use `]` to enter `pkg>` mode of Julia, then
```julia
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)
```
Owner
- Name: Abel Soares Siqueira
- Login: abelsiqueira
- Kind: user
- Location: Amsterdam - The Netherlands
- Company: Netherlands eScience Center
- Website: https://abelsiqueira.com
- Twitter: abel_siqueira
- Repositories: 331
- Profile: https://github.com/abelsiqueira