CUTEst input model

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No description provided.

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The following works:

julia> using CUTEst, JSOSuite
[ Info: Precompiling CUTEst [1b53aba6-35b6-5f92-a507-53c67d53f819]
[ Info: call set_mastsif() to use the full SIF collection
┌ Info: using problem repository
└   ENV["MASTSIF"] = ".julia/artifacts/a7ea0d0aaf29a39ca0fe75588fc077cdd5b5ed54/optrove-sif-99c5b38e7d03"

julia> nlp = CUTEstModel("ARGLINA")
  Problem name: ARGLINA
   All variables: ████████████████████ 200    All constraints: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
            free: ████████████████████ 200               free: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
           lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0                lower: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
           upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0                upper: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
         low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0              low/upp: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
           fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0                fixed: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
          infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0               infeas: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
            nnzh: (  0.00% sparsity)   20100           linear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
                                                    nonlinear: ⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅⋅ 0     
                                                         nnzj: (------% sparsity)         



julia> JSOSuite.select_solvers(nlp)
The problem ARGLINA has 200 variables and no constraints.
Algorithm selection:
- unconstrained: ✓;
- nonlinear objective: ✓;
- may use 2-th order derivative.
There are 9 solvers available:
["KNITRO", "LBFGS", "R2", "TRON", "TRUNK", "IPOPT", "DCISolver", "FletcherPenaltySolver", "Percival"].
9×14 DataFrame
 Row │ name                   name_solver     name_pkg                  solve_function  is_available  bounds  equalities  inequalities  specialized_nls  can_s ⋯
     │ String                 Symbol          String                    Symbol          Bool          Bool    Bool        Bool          Bool             Bool  ⋯
─────┼──────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
   1 │ KNITRO                 KnitroSolver    NLPModelsKnitro.jl        knitro                  true    true        true          true             true        ⋯
   2 │ LBFGS                  LBFGSSolver     JSOSolvers.jl             lbfgs                   true   false       false         false            false
   3 │ R2                     R2Solver        JSOSolvers.jl             R2                      true   false       false         false            false
   4 │ TRON                   TronSolver      JSOSolvers.jl             tron                    true    true       false         false            false
   5 │ TRUNK                  TrunkSolver     JSOSolvers.jl             trunk                   true   false       false         false            false        ⋯
   6 │ IPOPT                  IpoptSolver     NLPModelsIpopt.jl         ipopt                   true    true        true          true            false
   7 │ DCISolver              DCIWorkspace    DCISolver.jl              dci                     true   false        true         false            false
   8 │ FletcherPenaltySolver  FPSSSolver      FletcherPenaltySolver.jl  fps_solve               true   false        true         false            false
   9 │ Percival               PercivalSolver  Percival.jl               percival                true    true        true          true            false        ⋯
                                                                                                                                               5 columns omitted

julia> JSOSuite.solve("LBFGS", nlp)
"Execution stats: first-order stationary"

so this is just a documentation issue.