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See this problem from the rank_deficient.jl file
using ADNLPModels, CUTEst, NLPModels, NLPModelsIpopt, Test, LinearAlgebra #This package using FletcherPenaltyNLPSolver using Pkg; Pkg.update() @testset "Rank-deficient HS61" begin nlp = ADNLPModel( x -> 4 * x[1]^2 + 2 * x[2]^2 + 2 * x[3]^2 - 33 * x[1] + 16 * x[2] - 24 * x[3], zeros(3), x -> [3 * x[1] - 2 * x[2]^2 - 7; 4 * x[1] - x[3]^2 - 11], zeros(2), zeros(2), ) stats = fps_solve( nlp, nlp.meta.x0, #σ_0 = 1e3, #ρ_0 = 1e3, hessian_approx = Val(2), #error with hessian_approx = 1 ) [ Info: iter step f(x) ‖c(x)‖ ‖∇L‖ σ ρ δ stat η ‖λ‖ [ Info: 0 Init NaN 1.1e+01 3.3e+01 1.0e+00 1.0e+00 0.0e+00 Initial 0.0e+00 1.4e-309 [ Info: 0 Optml -4.8e+00 3.9e+00 1.1e+01 1.0e+00 1.0e+00 0.0e+00 SubOptimal 0.0e+00 5.7e+00 [ Info: 1 D -4.8e+00 3.9e+00 NaN 2.0e+00 2.0e+00 0.0e+00 SubOptimal 0.0e+00 5.7e+00 ┌ Warning: Error in StoppingInterface statuses: return status is unknown └ @ FletcherPenaltyNLPSolver ~/.julia/dev/FletcherPenaltyNLPSolver/src/StoppingInterfacemod.jl:142 stats.solver_specific = Dict{Symbol, Any}(:real_time => 0.026745080947875977, :internal_msg => :Restoration_Failed) ┌ Warning: Exception of unexpected failure: [:Unknown] └ @ FletcherPenaltyNLPSolver ~/.julia/dev/FletcherPenaltyNLPSolver/src/algo.jl:104 "Execution stats: unknown"
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See this problem from the rank_deficient.jl file
The text was updated successfully, but these errors were encountered: