This package provides optimization models based on NLPModels. The API can be found on their documentation page.
The models in this package specialize on modifying existing methods.
If you use NLPModelsModifiers.jl in your work, please cite using the format given in CITATION.cff.
The following models are implemented.
FeasibilityFormNLS: Creates residual variables and constraints, so that the residual is linear.FeasibilityResidual: Creates a nonlinear least squares model from an equality constrained problem in which the residual function is the constraints function.LBFGSModel: Creates a model using a LBFGS approximation to the Hessian using an existing NLPModel.LSR1Model: Creates a model using a LSR1 approximation to the Hessian using an existing NLPModel.SlackModel: Creates an equality constrained problem with bounds on the variables using an existing NLPModel.SlackNLSModel: Creates an equality constrained nonlinear least squares problem with bounds on the variables using an existing NLSModel.
See the documentation for details on the models.
pkg> add NLPModelsModifiersIf you think you found a bug, feel free to open an issue. 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. This forum is for general discussion about this repository and the JuliaSmoothOptimizers, so questions about any of our packages are welcome.