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Introduction of R2N Solver in JSOSolvers #288

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2 changes: 1 addition & 1 deletion Project.toml
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Expand Up @@ -16,7 +16,7 @@ SolverTools = "b5612192-2639-5dc1-abfe-fbedd65fab29"

[compat]
Krylov = "0.9.6"
LinearOperators = "2.0"
LinearOperators = "2.9"
NLPModels = "0.21"
NLPModelsModifiers = "0.7"
SolverCore = "0.3"
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3 changes: 2 additions & 1 deletion README.md
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Expand Up @@ -34,6 +34,7 @@ This package provides an implementation of four classic algorithms for unconstra
> high-order regularized models. *Mathematical Programming*, 163(1), 359-368.
> DOI: [10.1007/s10107-016-1065-8](https://doi.org/10.1007/s10107-016-1065-8)

- `R2N`: an inexact second-order quadratic regularization method for unconstrained optimization with shifted L-BFGS systems;
- `fomo`: a first-order method with momentum for unconstrained optimization;

- `tron`: a pure Julia implementation of TRON, a trust-region solver for bound-constrained optimization described in
Expand Down Expand Up @@ -63,7 +64,7 @@ using JSOSolvers, ADNLPModels

# Rosenbrock
nlp = ADNLPModel(x -> 100 * (x[2] - x[1]^2)^2 + (x[1] - 1)^2, [-1.2; 1.0])
stats = lbfgs(nlp) # or trunk, tron, R2
stats = lbfgs(nlp) # or trunk, tron, R2, R2N
```

## How to cite
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4 changes: 3 additions & 1 deletion docs/src/solvers.md
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Expand Up @@ -7,10 +7,11 @@
- [`trunk`](@ref)
- [`R2`](@ref)
- [`fomo`](@ref)
- [`R2N`](@ref)

| Problem type | Solvers |
| --------------------- | -------- |
| Unconstrained NLP | [`lbfgs`](@ref), [`tron`](@ref), [`trunk`](@ref), [`R2`](@ref), [`fomo`](@ref)|
| Unconstrained NLP | [`lbfgs`](@ref), [`tron`](@ref), [`trunk`](@ref), [`R2`](@ref), [`fomo`](@ref), ['R2N'] |
| Unconstrained NLS | [`trunk`](@ref), [`tron`](@ref) |
| Bound-constrained NLP | [`tron`](@ref) |
| Bound-constrained NLS | [`tron`](@ref) |
Expand All @@ -23,4 +24,5 @@ tron
trunk
R2
fomo
R2N
```
1 change: 1 addition & 0 deletions src/JSOSolvers.jl
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Expand Up @@ -45,6 +45,7 @@ end
include("lbfgs.jl")
include("trunk.jl")
include("fomo.jl")
include("R2N.jl")

# Unconstrained solvers for NLS
include("trunkls.jl")
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