NonlinearSolve.jl
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SciML
High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
Such that `makedocs` `warnonly = [:missing_docs, :cross_references]` can be removed.
This issue is based on the discussion in [here](https://discourse.julialang.org/t/how-does-modelingtoolkit-use-bounds-metadata/81487/8) The idea would be to support resolution of systems of nonlinear equations subject to contraints such as the ones available with...
This package is almost complete to be used in OrdinaryDiffEq.jl. For other discussions on this topic, see https://github.com/SciML/OrdinaryDiffEq.jl/issues/1570 However, there are some special things done in its nonlinear solvers which...
julia> supertype(supertype(NonlinearProblem)) SciMLBase.AbstractDEProblem
https://www.ams.org/journals/mcom/1970-24-109/S0025-5718-1970-0258276-9/ This might be putting it in the realm of NonlinearSolve instead, to keep the SimpleNonlinearSolve.jl version simple?
Add autoscaling option for trust region (and possibly other) methods.
We have an example of this in the paper, we just need to write it up as a tutorial.
**Is your feature request related to a problem?** Special Trust Region Algorithm for NLLS Problems with bound constraints. **Describe the solution you’d like** See https://nmayorov.wordpress.com/2015/06/19/trust-region-reflective-algorithm/ for a description of the...