https://github.com/juliasmoothoptimizers/cannoles.jl

Constrained and NoNlinear Optimizer of Least Squares
https://github.com/juliasmoothoptimizers/cannoles.jl

Last synced: 10 months ago
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Constrained and NoNlinear Optimizer of Least Squares

• Host: GitHub
• URL: https://github.com/juliasmoothoptimizers/cannoles.jl
• Owner: JuliaSmoothOptimizers
• License: other
• Created: 2019-03-19T18:39:42.000Z (over 7 years ago)
• Default Branch: main
• Last Pushed: 2025-06-04T23:28:25.000Z (about 1 year ago)
• Last Synced: 2025-09-05T05:32:38.444Z (11 months ago)
• Language: Julia
• Size: 3.05 MB
• Stars: 23
• Watchers: 4
• Forks: 6
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md
  • Citation: CITATION.cff

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README

          
# CaNNOLeS - Constrained and NoNlinear Optimizer of Least Squares

[![documentation](https://img.shields.io/badge/docs-stable-blue.svg)](https://JuliaSmoothOptimizers.github.io/CaNNOLeS.jl/stable)

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CaNNOLeS is a solver for equality-constrained nonlinear least-squares problems, i.e.,

optimization problems of the form

    min ¹/₂‖F(x)‖²      s. to     c(x) = 0.

It uses other JuliaSmoothOptimizers packages for development.

In particular, [NLPModels.jl](https://github.com/JuliaSmoothOptimizers/NLPModels.jl) is used for defining the problem, and [SolverCore](https://github.com/JuliaSmoothOptimizers/SolverCore.jl) for the output.

It also uses [HSL.jl](https://github.com/JuliaSmoothOptimizers/HSL.jl)'s `MA57` as main solver, but you can pass `linsolve=:ldlfactorizations` to use [LDLFactorizations.jl](https://github.com/JuliaSmoothOptimizers/LDLFactorizations.jl).

## References

> Orban, D., & Siqueira, A. S.

> A Regularization Method for Constrained Nonlinear Least Squares.

> Computational Optimization and Applications 76, 961–989 (2020).

> [10.1007/s10589-020-00201-2](https://doi.org/10.1007/s10589-020-00201-2)

If you use CaNNOLeS.jl in your work, please cite using the format given in [CITATION.cff](CITATION.cff).

## Installation

1. Follow [HSL.jl](https://github.com/JuliaSmoothOptimizers/HSL.jl)'s `MA57` installation if possible. Otherwise [LDLFactorizations.jl](https://github.com/JuliaSmoothOptimizers/LDLFactorizations.jl) will be used.

2. `pkg> add CaNNOLeS`

## Examples

```julia

using CaNNOLeS, ADNLPModels

# Rosenbrock

nls = ADNLSModel(x -> [x[1] - 1; 10 * (x[2] - x[1]^2)], [-1.2; 1.0], 2)

stats = cannoles(nls)

# Constrained

nls = ADNLSModel(

  x -> [x[1] - 1; 10 * (x[2] - x[1]^2)],

  [-1.2; 1.0],

  2,

  x -> [x[1] * x[2] - 1],

  [0.0],

  [0.0],

)

stats = cannoles(nls)

```

# Bug reports and discussions

If you think you found a bug, feel free to open an [issue](https://github.com/JuliaSmoothOptimizers/CaNNOLeS.jl/issues).

Focused suggestions and requests can also be opened as issues. Before opening a pull request, start an issue or a discussion on the topic, please.

If you want to ask a question not suited for a bug report, feel free to start a discussion [here](https://github.com/JuliaSmoothOptimizers/Organization/discussions). This forum is for general discussion about this repository and the [JuliaSmoothOptimizers](https://github.com/JuliaSmoothOptimizers), so questions about any of our packages are welcome.