CUTEst Unbounded Constrained Nonlinear Optimization Benchmarks
Introduction
CUTEst, the Constraind and Unconstrained Testing Environment is, as the name suggests is a collection of around 1500 problems for general nonlinear optimization used to test optimization routines. The wrapper CUTEst.jl provides convenient access to the problem collection, which we can leverage to test the optimizers made available by Optimization.jl.
This benchmark uses the following packages:
Benchmarks
using Optimization
using OptimizationNLPModels
using CUTEst
using OptimizationOptimJL
using Ipopt
using OptimizationMOI
using OptimizationMOI: MOI as MOI
using DataFrames
using Plots
using StatsPlots
using StatsBase: countmapBenchmarks
using DataFrames
# Only Ipopt supports constraints; use only Ipopt for constrained problems
optimizers = [
("Ipopt", MOI.OptimizerWithAttributes(Ipopt.Optimizer,
"max_iter" => 5000,
"tol" => 1e-6,
"print_level" => 5)),
]
function get_stats(sol, optimizer_name)
if hasfield(typeof(sol), :stats) && hasfield(typeof(sol.stats), :time)
solve_time = sol.stats.time
else
solve_time = NaN
end
return (length(sol.u), solve_time, optimizer_name, Symbol(sol.retcode))
end
function run_benchmarks(problems, optimizers; chunk_size=3)
problem = String[]
n_vars = Int64[]
secs = Float64[]
solver = String[]
retcode = Symbol[]
optz = length(optimizers)
n = length(problems)
@info "Processing $(n) problems with $(optz) optimizers in chunks of $(chunk_size)"
broadcast(c -> sizehint!(c, optz * n), [problem, n_vars, secs, solver, retcode])
for chunk_start in 1:chunk_size:n
chunk_end = min(chunk_start + chunk_size - 1, n)
chunk_problems = problems[chunk_start:chunk_end]
@info "Processing chunk $(div(chunk_start-1, chunk_size)+1)/$(div(n-1, chunk_size)+1): problems $(chunk_start)-$(chunk_end)"
for (idx, prob_name) in enumerate(chunk_problems)
current_problem = chunk_start + idx - 1
@info "Problem $(current_problem)/$(n): $(prob_name)"
nlp_prob = nothing
try
nlp_prob = CUTEstModel(prob_name)
if nlp_prob.meta.nvar > 10000
@info " Skipping $(prob_name) (too large: $(nlp_prob.meta.nvar) variables)"
finalize(nlp_prob)
continue
end
prob = OptimizationNLPModels.OptimizationProblem(nlp_prob, Optimization.AutoFiniteDiff())
for (optimizer_name, optimizer) in optimizers
try
sol = solve(prob, optimizer; maxiters = 1000, maxtime = 30.0)
@info "✓ Solved $(prob_name) with $(optimizer_name) - Status: $(sol.retcode)"
vars, time, alg, code = get_stats(sol, optimizer_name)
push!(problem, prob_name)
push!(n_vars, vars)
push!(secs, time)
push!(solver, alg)
push!(retcode, code)
catch e
push!(problem, prob_name)
push!(n_vars, nlp_prob !== nothing ? nlp_prob.meta.nvar : -1)
push!(secs, NaN)
push!(solver, optimizer_name)
push!(retcode, :FAILED)
end
end
catch e
for (optimizer_name, optimizer) in optimizers
push!(problem, prob_name)
push!(n_vars, -1)
push!(secs, NaN)
push!(solver, optimizer_name)
push!(retcode, :LOAD_FAILED)
end
finally
if nlp_prob !== nothing
try
finalize(nlp_prob)
catch e
end
end
end
end
GC.gc()
@info "Completed chunk, memory usage cleaned up"
end
return DataFrame(problem = problem, n_vars = n_vars, secs = secs, solver = solver, retcode = retcode)
endrun_benchmarks (generic function with 1 method)Equality/Inequality constrained problems with unbounded variables
These problems have a constraint function that's subject to either equality or inequality constraints, but the variables themselves are free. CUTEst contains 285 problems with equality constraints and 114 with inequality constraints for a total of 299.
We start by analyzing the equality-constrained problems, of which there are 285. The following figure shows the time to solution as a function of number of variables by optimizer.
using DataFrames
all_eq_unb_problems = CUTEst.select_sif_problems(min_con=1, only_equ_con=true, only_free_var=true)
println("Available equality-constrained, unbounded problems:")
println(all_eq_unb_problems)
eq_unb_problems = all_eq_unb_problems[1:min(10, length(all_eq_unb_problems))]
# Remove the 8th problem if it is 'luk' or 'lukvle8' (case-insensitive)
if length(eq_unb_problems) >= 8 && (lowercase(eq_unb_problems[8]) == "luk" || lowercase(eq_unb_problems[8]) == "lukvle8")
eq_unb_problems = vcat(eq_unb_problems[1:7], eq_unb_problems[9:end])
end
@info "Testing $(length(eq_unb_problems)) equality-constrained unbounded problems"
# Analysis
eq_unb_results = run_benchmarks(eq_unb_problems, optimizers)
# Show full results table
println("Full results table for equality-constrained problems:")
display(eq_unb_results)
# Calculate and display success rates for equality constrained
successful_codes = [:Success, :MaxIters, :MaxTime, :FirstOrderOptimal]
successful_results = filter(row -> row.retcode in successful_codes, eq_unb_results)
total_attempts = nrow(eq_unb_results)
successful_attempts = nrow(successful_results)
success_rate = total_attempts > 0 ? round(successful_attempts / total_attempts * 100, digits=1) : 0
@info "EQUALITY CONSTRAINED SUCCESS RATE: $(success_rate)% ($(successful_attempts)/$(total_attempts))"
@df eq_unb_results scatter(:n_vars, :secs,
group = :solver,
xlabel = "n. variables",
ylabel = "secs.",
title = "Time to solution by optimizer and number of vars",
)
if nrow(eq_unb_results) > 0
try
@df eq_unb_results scatter(:n_vars, :secs,
group = :solver,
xlabel = "n. variables",
ylabel = "secs.",
title = "Time to solution by optimizer and number of vars",
)
println("Plotted equality-constrained results.")
catch e
println("Plotting failed: ", e)
end
else
println("Warning: equality-constrained results DataFrame is empty. No data to plot.")
println("Attempted problems:")
println(eq_unb_problems)
endAvailable equality-constrained, unbounded problems:
["GAUSS2", "MSS1", "WAYSEA1NE", "FBRAIN2", "BROWNDENE", "AUG2D", "HS79", "L
UKVLE8", "GULFNE", "JUDGENE", "STRTCHDVNE", "TRIGON1NE", "PENLT1NE", "PATTE
RNNE", "BA-L1SP", "EXPFITNE", "SSINE", "LUKSAN17", "HS7", "BOX3NE", "MODBEA
LENE", "KSS", "HS48", "BT9", "S308NE", "LUKVLE7", "MGH17S", "DENSCHNDNE", "
CERI651B", "YATP1CNE", "THURBER", "VESUVIOU", "CERI651E", "ENSO", "BARDNE",
"GOTTFR", "ORTHRDS2C", "SPINOP", "STREGNE", "PENLT2NE", "HS42", "WOODSNE",
"HS27", "GRIDNETH", "LUKVLE4C", "EIGENA2", "DENSCHNBNE", "DIXCHLNG", "VARD
IMNE", "COATINGNE", "HIMMELBE", "CYCLIC3", "YATP2CNE", "CHWIRUT1", "CERI651
A", "MISRA1C", "SPIN2", "HATFLDG", "BT11", "MNISTS0", "SPIN2OP", "ORTHREGC"
, "LUKVLE17", "MARATOS", "JENSMPNE", "MANCINONE", "LSC1", "CHWIRUT2", "BT6"
, "ORTHREGB", "LUKVLI4", "HS6", "LUKSAN12", "HS28", "NELSON", "LUKVLE15", "
WATSONNE", "NONDIANE", "10FOLDTR", "DEVGLA1NE", "CUBENE", "HS40", "ELATVIDU
NE", "HATFLDF", "MOREBVNE", "KOWOSBNE", "DMN37142", "LIARWHDNE", "COOLHANS"
, "MSS3", "HS8", "BT8", "MSS2", "ARWHDNE", "BT1", "LSC2", "CHAINWOONE", "HA
HN1", "KIRBY2", "VESUVIA", "MISRA1A", "DEVGLA2NE", "DMN37143", "CERI651C",
"ORTHRDS2", "BROYDNBD", "EGGCRATENE", "EIGENBCO", "LUKVLE1", "DIAMON3D", "R
ECIPE", "HATFLDFLNE", "DENSCHNENE", "ORTHRGDM", "VESUVIO", "PRICE4NE", "GRI
DNETE", "ARGLCLE", "CHNRSBNE", "GBRAIN", "EIGENC", "BROWNBSNE", "ARGTRIG",
"BYRDSPHR", "RAT43", "LUKSAN21", "LUKVLE6", "AUG3D", "HS50", "METHANB8", "P
OWELLSQ", "ECKERLE4", "CHANDHEU", "BT10", "MNISTS5", "BOXBOD", "DANIWOOD",
"OSCIPANE", "SROSENBRNE", "LUKSAN13", "HS26", "CERI651D", "BT7", "LCH", "BR
YBNDNE", "LUKVLE2", "HS9", "MUONSINE", "HS100LNP", "BA-L73", "LUKVLE16", "G
ENHS28", "LUKVLE14", "MGH10", "BT5", "GROWTH", "POWELLBS", "HS61", "ORTHREG
A", "ORTHREGD", "DMN15102", "PRICE3NE", "BA-L21", "EIGENB2", "FBRAIN", "LUK
VLE9", "HS77", "INTEQNE", "ENGVAL2NE", "HYDCAR20", "HS39", "MSQRTA", "YATP2
SQ", "OSBORNE2", "AUG3DC", "ARGAUSS", "CHNRSNBMNE", "GENROSENE", "MWRIGHT",
"DMN15333", "BEALENE", "LUKSAN22", "BT4", "TRIGON2NE", "BT2", "YATP1NE", "
YFITNE", "DENSCHNCNE", "HATFLDENE", "WAYSEA2NE", "LUKSAN14", "LUKSAN11", "H
S46", "SPMSQRT", "POWELLSE", "DIAMON2D", "EIGENC2", "HS49", "ELEC", "SBRYBN
DNE", "FBRAIN3", "CYCLOOCF", "ROSZMAN1", "EIGENCCO", "MEYER3NE", "ARGLBLE",
"MISRA1D", "EIGENAU", "LANCZOS2", "HS78", "BENNETT5", "BOOTH", "OSBORNE1",
"BA-L1", "ERRINROSNE", "DMN15332", "ZANGWIL3", "LUKVLE12", "MGH10S", "LUKV
LE10", "LUKVLE13", "DENSCHNFNE", "HIMMELBC", "LANCZOS3", "HYPCIR", "HEART6"
, "MSQRTB", "TQUARTICNE", "BIGGS6NE", "OSCIGRNE", "LANCZOS1", "GRIDNETB", "
ARGLALE", "S316-322", "HIMMELBD", "ORTHRDM2", "LUKVLE4", "FLT", "LUKSAN15",
"FREURONE", "SSBRYBNDNE", "DANWOOD", "LUKVLE3", "ORTHRGDS", "HYDCAR6", "VI
BRBEAMNE", "HEART8", "EIGENACO", "VANDANIUMS", "HELIXNE", "EIGENB", "BROWNA
LE", "BA-L49", "SPIN", "RSNBRNE", "LUKVLE11", "CLUSTER", "BDQRTICNE", "RAT4
2", "BA-L16", "METHANL8", "HS51", "QINGNE", "HS56", "NONMSQRTNE", "BT12", "
GAUSS3", "HATFLDDNE", "HIMMELBA", "GAUSS1", "HS111LNP", "HS52", "MISRA1B",
"SINVALNE", "EXP2NE", "LUKVLE18", "BA-L52", "LUKSAN16", "HIMMELBFNE", "MGH0
9", "ERRINRSMNE", "POWERSUMNE", "BROYDN3D", "DMN15103", "AUG2DC", "HS47", "
MGH17", "EXTROSNBNE", "BT3"]
***************************************************************************
***
This program contains Ipopt, a library for large-scale nonlinear optimizati
on.
Ipopt is released as open source code under the Eclipse Public License (EP
L).
For more information visit https://github.com/coin-or/Ipopt
***************************************************************************
***
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 2000
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 36
Exception of type: TOO_FEW_DOF in file "Interfaces/IpIpoptApplication.cpp"
at line 662:
Exception message: status != TOO_FEW_DEGREES_OF_FREEDOM evaluated false: T
oo few degrees of freedom (rethrown)!
EXIT: Problem has too few degrees of freedom.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 6570
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 4095
Total number of variables............................: 90
variables with only lower bounds: 0
variables with lower and upper bounds: 0
variables with only upper bounds: 0
Total number of equality constraints.................: 73
Total number of inequality constraints...............: 0
inequality constraints with only lower bounds: 0
inequality constraints with lower and upper bounds: 0
inequality constraints with only upper bounds: 0
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
0 -4.0500000e+03 8.90e+01 9.00e+01 -1.0 0.00e+00 - 0.00e+00 0.00e+0
0 0
1 -1.0343731e+03 2.20e+01 4.86e+04 -1.0 4.98e-01 - 1.00e+00 1.00e+0
0h 1
2 -4.4135894e+02 9.41e+00 1.17e+09 -1.0 3.00e-01 10.0 1.00e+00 1.00e+0
0h 1
3 -1.1520127e+02 1.35e+01 6.32e+13 -1.0 1.55e+00 11.3 1.00e+00 1.00e+0
0h 1
4 -1.6856914e+01 7.44e+00 2.15e+15 -1.0 1.18e+00 14.5 1.00e+00 1.00e+0
0h 1
5 -4.8353640e+00 1.67e+00 1.49e+16 -1.0 4.88e-01 16.7 1.00e+00 1.00e+0
0h 1
6 -2.1731031e+00 3.49e-01 2.31e+16 -1.0 2.29e-01 17.1 1.00e+00 1.00e+0
0h 1
7 -1.3500739e+00 6.30e-02 1.18e+17 -1.0 1.01e-01 17.5 1.00e+00 1.00e+0
0h 1
8 -9.0323387e-01 1.64e-02 1.16e+17 -1.0 6.72e-02 18.0 1.00e+00 1.00e+0
0h 1
9 -8.0652706e-01 2.07e-03 1.15e+17 -1.0 2.10e-02 18.4 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
10 -8.3089391e-01 2.15e-04 2.94e+17 -1.0 7.97e-03 17.9 1.00e+00 1.00e+0
0h 1
11 -8.4099177e-01 4.14e-05 1.06e+17 -1.0 3.82e-03 17.4 1.00e+00 1.00e+0
0h 1
12 -8.4575518e-01 1.05e-05 1.18e+18 -1.7 1.94e-03 17.0 1.00e+00 1.00e+0
0h 1
WARNING: Problem in step computation; switching to emergency mode.
13r-8.4575518e-01 1.05e-05 9.86e+02 -3.8 0.00e+00 19.2 0.00e+00 0.00e+0
0R 1
14r-8.4607237e-01 1.87e-06 1.75e+00 -3.8 1.61e-02 - 1.00e+00 1.43e-0
2f 1
15 -8.4607237e-01 1.87e-06 1.48e+02 -3.8 3.50e-18 19.6 1.00e+00 1.00e+0
0 0
16 -8.4607237e-01 1.87e-06 2.96e+02 -3.8 2.10e-17 19.1 1.00e+00 1.00e+0
0 0
17 -8.4607237e-01 1.87e-06 4.44e+02 -3.8 9.43e-17 18.7 1.00e+00 1.00e+0
0 0
18 -8.4607237e-01 1.87e-06 5.92e+02 -3.8 3.77e-16 18.2 1.00e+00 1.00e+0
0 0
19 -8.4607237e-01 1.87e-06 7.40e+02 -3.8 1.41e-15 17.7 1.00e+00 1.00e+0
0 0
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
20r-8.4607237e-01 1.87e-06 9.23e+02 -3.8 0.00e+00 17.2 0.00e+00 4.77e-0
7R 22
21r-8.4755616e-01 1.91e-06 1.03e+00 -3.8 1.13e-02 - 1.00e+00 8.27e-0
2f 1
22r-8.4909450e-01 7.51e-07 7.86e-06 -3.8 4.85e-04 - 1.00e+00 1.00e+0
0h 1
23r-8.4909450e-01 7.51e-07 8.20e+02 -3.8 0.00e+00 16.8 0.00e+00 4.77e-0
7R 22
24r-8.4931084e-01 8.86e-08 2.18e-02 -3.8 3.27e-04 - 1.00e+00 2.18e-0
1f 1
25 -8.4931084e-01 8.86e-08 7.40e+01 -3.8 3.82e-15 16.3 1.00e+00 1.00e+0
0h 1
26 -8.4931084e-01 8.86e-08 1.49e+02 -3.8 2.30e-14 15.8 1.00e+00 1.00e+0
0h 1
27 -8.4931084e-01 8.86e-08 2.23e+02 -3.8 1.04e-13 15.3 1.00e+00 1.00e+0
0h 1
28 -8.4931084e-01 8.86e-08 2.98e+02 -3.8 4.15e-13 14.9 1.00e+00 1.00e+0
0h 1
29 -8.4931084e-01 8.86e-08 3.72e+02 -3.8 1.56e-12 14.4 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
30 -8.4931084e-01 8.86e-08 4.47e+02 -3.8 5.60e-12 13.9 1.00e+00 1.00e+0
0h 1
31 -8.4931084e-01 8.86e-08 5.21e+02 -3.8 1.96e-11 13.4 1.00e+00 1.00e+0
0h 1
32 -8.4931084e-01 8.86e-08 5.95e+02 -3.8 6.72e-11 12.9 1.00e+00 1.00e+0
0h 1
33 -8.4931084e-01 8.86e-08 6.69e+02 -3.8 2.26e-10 12.5 1.00e+00 1.00e+0
0h 1
34 -8.4931085e-01 8.86e-08 7.40e+02 -3.8 7.51e-10 12.0 1.00e+00 1.00e+0
0h 1
35 -8.4931085e-01 8.86e-08 8.01e+02 -3.8 2.44e-09 11.5 1.00e+00 1.00e+0
0h 1
36 -8.4931088e-01 8.86e-08 8.36e+02 -3.8 7.64e-09 11.0 1.00e+00 1.00e+0
0h 1
37 -8.4931094e-01 8.86e-08 7.91e+02 -3.8 2.17e-08 10.6 1.00e+00 1.00e+0
0h 1
38 -8.4931109e-01 1.97e-07 5.75e+02 -3.8 4.73e-08 10.1 1.00e+00 1.00e+0
0h 1
39 -8.4931126e-01 3.53e-07 1.89e+02 -3.8 4.67e-08 9.6 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
40 -8.4931126e-01 2.23e-07 5.47e+01 -3.8 4.05e-08 9.1 1.00e+00 1.00e+0
0h 1
41 -1.1785535e+01 2.14e+01 1.14e+12 -3.8 2.72e+00 - 1.00e+00 1.00e+0
0f 1
42 -3.3071569e+00 5.21e+00 7.78e+15 -3.8 1.26e+00 8.7 1.00e+00 1.00e+0
0h 1
43 -2.0175689e+00 1.15e+00 1.98e+17 -3.8 5.58e-01 10.0 1.00e+00 1.00e+0
0h 1
44 -1.0077496e+00 1.63e-01 2.29e+17 -3.8 2.15e-01 11.3 1.00e+00 1.00e+0
0h 1
45 -8.5613530e-01 1.26e-01 2.44e+17 -3.8 1.07e-01 - 1.00e+00 2.50e-0
1h 3
46 -8.5232312e-01 1.10e-01 2.21e+17 -3.8 5.86e-02 - 1.00e+00 1.25e-0
1h 4
47 -8.4937224e-01 1.09e-01 2.18e+17 -3.8 6.52e-02 - 1.00e+00 1.56e-0
2h 7
48 -8.4933815e-01 1.09e-01 2.18e+17 -3.8 6.59e-02 - 1.00e+00 1.22e-0
4h 14
49 -8.4932335e-01 1.09e-01 2.18e+17 -3.8 5.75e-02 - 1.00e+00 4.88e-0
4h 12
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
50 -7.9323599e-01 9.48e-03 2.85e+17 -3.8 6.23e-02 - 1.00e+00 1.00e+0
0h 1
51 -7.6628377e-01 2.85e-04 7.16e+18 -3.8 8.89e-03 11.7 1.00e+00 1.00e+0
0h 1
52 -7.3738392e-01 2.06e-04 4.55e+19 -3.8 1.00e-02 12.2 1.00e+00 1.00e+0
0h 1
53 -7.4904075e-01 1.66e-04 4.54e+23 -3.8 8.00e-03 12.6 1.00e+00 1.00e+0
0h 1
54 -7.5469055e-01 2.74e-05 1.80e+23 -3.8 2.61e-03 13.0 1.00e+00 1.00e+0
0h 1
55 -7.5885366e-01 6.40e-06 7.11e+25 -3.8 1.50e-03 13.4 1.00e+00 1.00e+0
0h 1
WARNING: Problem in step computation; switching to emergency mode.
56r-7.5885366e-01 6.40e-06 9.77e+02 -3.8 0.00e+00 19.3 0.00e+00 0.00e+0
0R 1
57r-7.5885354e-01 7.13e-07 1.99e-01 -3.8 3.35e-04 - 1.00e+00 2.35e-0
2f 1
58 -2.5756948e+00 2.27e-02 1.36e+02 -3.8 4.57e-02 2.0 1.00e+00 1.00e+0
0f 1
59 -1.9498025e+00 6.72e-03 2.85e+07 -3.8 2.64e-02 3.3 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
60 -1.6902911e+00 1.39e-03 1.10e+07 -3.8 1.30e-02 3.8 1.00e+00 1.00e+0
0h 1
61 -1.5976794e+00 4.40e-04 2.65e+08 -3.8 8.03e-03 3.3 1.00e+00 1.00e+0
0h 1
62 -1.6653195e+00 2.63e-04 3.66e+12 -3.8 6.11e-03 2.8 1.00e+00 1.00e+0
0f 1
63 -1.9910376e+00 2.26e-03 3.83e+15 -3.8 2.34e-02 2.3 1.00e+00 1.00e+0
0f 1
64 -1.9780188e+00 1.02e-04 3.08e+17 -3.8 5.72e-03 4.6 1.00e+00 1.00e+0
0h 1
65 -1.9110760e+00 1.15e-04 4.09e+19 -3.8 5.45e-03 4.1 1.00e+00 1.00e+0
0H 1
66 -1.9099997e+00 3.97e-05 6.18e+20 -3.8 3.28e-03 3.6 1.00e+00 1.00e+0
0h 1
67 -1.9053531e+00 9.91e-06 9.01e+22 -3.8 1.59e-03 5.8 1.00e+00 1.00e+0
0h 1
68 -1.9009236e+00 5.92e-06 3.29e+28 -3.8 9.71e-04 6.3 1.00e+00 1.00e+0
0h 1
69 -1.9048529e+00 4.78e-06 5.69e+30 -3.8 1.33e-03 6.7 1.00e+00 1.00e+0
0f 1
WARNING: Problem in step computation; switching to emergency mode.
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
70r-1.9048529e+00 4.78e-06 9.69e+02 -3.8 0.00e+00 18.5 0.00e+00 0.00e+0
0R 1
71r-1.9047160e+00 5.38e-07 1.50e-02 -3.8 1.11e-03 - 1.00e+00 3.16e-0
2f 1
72 -4.2551342e+00 2.69e-02 1.93e+02 -3.8 6.61e-02 2.0 1.00e+00 1.00e+0
0f 1
73 -3.7488224e+00 3.27e-03 1.27e+07 -3.8 2.23e-02 3.3 1.00e+00 1.00e+0
0h 1
74 -3.7805878e+00 9.56e-04 4.04e+06 -3.8 1.08e-02 2.9 1.00e+00 1.00e+0
0h 1
75 -3.9921881e+00 6.76e-03 1.23e+10 -3.8 3.52e-02 2.4 1.00e+00 1.00e+0
0f 1
76 -3.8390058e+00 5.34e-04 4.18e+10 -3.8 9.88e-03 3.7 1.00e+00 1.00e+0
0h 1
77 -3.8489717e+00 8.30e-04 2.83e+13 -3.8 1.12e-02 3.2 1.00e+00 1.00e+0
0h 1
78 -3.7455376e+00 4.06e-04 2.19e+16 -3.8 1.20e-02 5.5 1.00e+00 1.00e+0
0h 1
79 -3.7146108e+00 3.48e-05 8.24e+16 -3.8 3.98e-03 6.8 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
80 -1.3907502e+06 1.77e+06 2.50e+33 -3.8 1.13e+00 6.3 1.00e+00 1.00e+0
0H 1
WARNING: Problem in step computation; switching to emergency mode.
81r-1.3907502e+06 1.77e+06 9.99e+02 6.2 0.00e+00 18.2 0.00e+00 0.00e+0
0R 1
82r-2.4249821e+05 4.92e+05 6.54e+02 6.2 1.80e+09 - 1.00e+00 9.74e-0
4f 1
83 -2.4248985e+05 4.92e+05 5.23e+17 -3.8 1.10e-02 19.7 1.00e+00 1.00e+0
0h 1
WARNING: Problem in step computation; switching to emergency mode.
84r-2.4248985e+05 4.92e+05 9.99e+02 5.7 0.00e+00 19.2 0.00e+00 0.00e+0
0R 1
85r-3.9495593e+04 1.87e+05 3.15e+02 5.7 4.93e+08 - 1.00e+00 9.87e-0
4f 1
86 -3.9495016e+04 1.87e+05 8.54e+16 -3.8 2.01e-03 19.6 1.00e+00 1.00e+0
0h 1
WARNING: Problem in step computation; switching to emergency mode.
87r-3.9495016e+04 1.87e+05 9.99e+02 5.3 0.00e+00 19.1 0.00e+00 0.00e+0
0R 1
88r-7.7474545e+04 1.02e+05 8.86e+02 5.3 1.85e+08 - 1.00e+00 9.98e-0
4f 1
89r-7.7474545e+04 1.02e+05 9.99e+02 5.0 0.00e+00 19.6 0.00e+00 4.77e-0
7R 22
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
90r-1.7880495e+04 4.80e+04 4.14e+02 5.0 1.01e+08 - 1.00e+00 9.97e-0
4f 1
91 -1.7880252e+04 4.80e+04 7.98e+15 -3.8 6.35e-04 19.1 1.00e+00 1.00e+0
0h 1
92 -1.7880080e+04 4.80e+04 1.60e+16 -3.8 4.77e-04 19.5 1.00e+00 1.00e+0
0h 1
93r-1.7880080e+04 4.80e+04 9.99e+02 4.7 0.00e+00 20.0 0.00e+00 4.77e-0
7R 22
94r-5.3224086e+04 2.25e+04 9.93e+02 4.7 4.58e+07 - 2.35e-01 1.04e-0
3f 1
95r-5.3224086e+04 2.25e+04 9.99e+02 4.4 0.00e+00 19.5 0.00e+00 4.77e-0
7R 22
96r-4.1811005e+04 3.12e+04 9.79e+02 4.4 1.99e+07 - 9.62e-02 1.12e-0
3f 1
97r-2.1791348e+04 1.14e+04 7.89e+05 3.0 7.03e+01 4.0 8.22e-01 1.00e+0
0f 1
98r-2.1791348e+04 1.14e+04 9.99e+02 4.1 0.00e+00 19.0 0.00e+00 4.77e-0
7R 22
99r-5.7835348e+03 7.51e+03 6.56e+02 4.1 1.12e+07 - 1.00e+00 1.01e-0
3f 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
100r-5.7835348e+03 7.51e+03 9.99e+02 3.9 0.00e+00 18.5 0.00e+00 4.77e-0
7R 22
101r-3.1704702e+04 1.02e+04 9.82e+02 3.9 5.55e+06 - 1.48e-01 1.34e-0
3f 1
102r-3.0785995e+03 5.34e+03 2.28e+05 2.5 6.41e+01 4.0 6.55e-01 1.00e+0
0f 1
103 -3.0785427e+03 5.33e+03 2.51e+14 -3.8 2.27e-04 18.0 1.00e+00 1.00e+0
0h 1
104 -3.0782158e+03 5.33e+03 5.01e+14 -3.8 1.37e-03 17.6 1.00e+00 1.00e+0
0h 1
105 -3.0780342e+03 5.33e+03 7.52e+14 -3.8 7.67e-04 18.0 1.00e+00 1.00e+0
0h 1
106 -3.0779262e+03 5.33e+03 1.00e+15 -3.8 3.85e-04 18.4 1.00e+00 1.00e+0
0h 1
107 -3.0778839e+03 5.33e+03 1.25e+15 -3.8 1.80e-04 18.8 1.00e+00 1.00e+0
0h 1
108r-3.0778839e+03 5.33e+03 9.99e+02 3.7 0.00e+00 19.3 0.00e+00 4.77e-0
7R 22
109r-2.1478572e+04 7.23e+03 3.66e+03 3.7 2.27e+06 - 9.26e-03 2.32e-0
3f 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
110r-5.3887006e+03 2.83e+03 1.29e+07 2.3 3.36e+01 6.0 7.69e-01 1.00e+0
0f 1
111r-5.3887006e+03 2.83e+03 9.99e+02 3.5 0.00e+00 18.8 0.00e+00 4.77e-0
7R 22
112r-1.0991572e+03 6.44e+03 1.28e+03 3.5 8.99e+05 - 2.06e-02 3.12e-0
3f 1
113r-1.1785648e+03 1.92e+03 9.17e+06 2.8 2.05e+01 6.0 8.31e-01 1.00e+0
0f 1
114r-1.1785648e+03 1.92e+03 9.99e+02 3.3 0.00e+00 18.3 0.00e+00 4.77e-0
7R 22
115r-1.2789154e+03 2.74e+03 9.91e+02 3.3 9.49e+05 - 1.33e-02 2.00e-0
3f 1
116r-1.9103757e+02 9.58e+02 6.05e+06 1.9 2.14e+01 6.0 5.94e-01 1.00e+0
0f 1
117r-1.9103757e+02 9.58e+02 9.99e+02 3.0 0.00e+00 17.8 0.00e+00 4.77e-0
7R 22
118r-8.7984967e+02 2.01e+03 1.18e+03 3.0 2.69e+05 - 3.22e-02 3.53e-0
3f 1
119r-3.0084178e+02 7.10e+02 8.50e+06 2.3 2.39e+01 6.0 4.02e-01 1.00e+0
0f 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
120 -3.0083831e+02 7.10e+02 1.69e+13 -3.8 7.36e-05 17.4 1.00e+00 1.00e+0
0h 1
121 -3.0081812e+02 7.09e+02 3.38e+13 -3.8 4.41e-04 16.9 1.00e+00 1.00e+0
0h 1
122 -3.0071630e+02 7.09e+02 5.06e+13 -3.8 1.99e-03 16.4 1.00e+00 1.00e+0
0h 1
123 -3.0067101e+02 7.09e+02 6.75e+13 -3.8 9.94e-04 16.8 1.00e+00 1.00e+0
0h 1
124 -3.0044110e+02 7.09e+02 8.43e+13 -3.8 3.70e-03 16.4 1.00e+00 1.00e+0
0h 1
125 -3.0035975e+02 7.09e+02 1.01e+14 -3.8 1.67e-03 16.8 1.00e+00 1.00e+0
0h 1
126 -3.0032315e+02 7.08e+02 1.18e+14 -3.8 7.33e-04 17.2 1.00e+00 1.00e+0
0h 1
127 -3.0019674e+02 7.08e+02 1.35e+14 -3.8 2.51e-03 16.7 1.00e+00 1.00e+0
0h 1
128 -3.0014022e+02 7.08e+02 1.52e+14 -3.8 1.06e-03 17.2 1.00e+00 1.00e+0
0h 1
129 -3.0011811e+02 7.08e+02 1.68e+14 -3.8 4.41e-04 17.6 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
130 -3.0004893e+02 7.08e+02 1.85e+14 -3.8 1.46e-03 17.1 1.00e+00 1.00e+0
0h 1
131 -3.0002286e+02 7.08e+02 2.02e+14 -3.8 5.95e-04 17.5 1.00e+00 1.00e+0
0h 1
132 -3.0001163e+02 7.08e+02 2.19e+14 -3.8 2.42e-04 18.0 1.00e+00 1.00e+0
0h 1
133 -2.9997195e+02 7.08e+02 2.36e+14 -3.8 7.81e-04 17.5 1.00e+00 1.00e+0
0h 1
134 -2.9995701e+02 7.08e+02 2.52e+14 -3.8 3.14e-04 17.9 1.00e+00 1.00e+0
0h 1
135 -2.9995098e+02 7.08e+02 2.69e+14 -3.8 1.26e-04 18.3 1.00e+00 1.00e+0
0h 1
136 -2.9993052e+02 7.08e+02 2.86e+14 -3.8 4.00e-04 17.9 1.00e+00 1.00e+0
0h 1
137 -2.9987459e+02 7.07e+02 3.03e+14 -3.8 1.27e-03 17.4 1.00e+00 1.00e+0
0h 1
138 -2.9985072e+02 7.07e+02 3.20e+14 -3.8 5.03e-04 17.8 1.00e+00 1.00e+0
0h 1
139 -2.9975445e+02 7.07e+02 3.36e+14 -3.8 1.58e-03 17.3 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
140 -2.9972596e+02 7.07e+02 3.53e+14 -3.8 6.25e-04 17.8 1.00e+00 1.00e+0
0h 1
141 -2.9963243e+02 7.07e+02 3.70e+14 -3.8 1.96e-03 17.3 1.00e+00 1.00e+0
0h 1
142 -2.9959457e+02 7.07e+02 3.87e+14 -3.8 7.68e-04 17.7 1.00e+00 1.00e+0
0h 1
143 -2.9943715e+02 7.07e+02 4.03e+14 -3.8 2.41e-03 17.2 1.00e+00 1.00e+0
0h 1
144 -2.9939016e+02 7.06e+02 4.20e+14 -3.8 9.40e-04 17.6 1.00e+00 1.00e+0
0h 1
145 -2.9937293e+02 7.06e+02 4.37e+14 -3.8 3.67e-04 18.1 1.00e+00 1.00e+0
0h 1
146 -2.9936607e+02 7.06e+02 4.54e+14 -3.8 1.43e-04 18.5 1.00e+00 1.00e+0
0h 1
147 -2.9934658e+02 7.06e+02 4.70e+14 -3.8 4.45e-04 18.0 1.00e+00 1.00e+0
0h 1
148 -2.9924606e+02 7.06e+02 4.87e+14 -3.8 1.38e-03 17.5 1.00e+00 1.00e+0
0h 1
149 -2.9922004e+02 7.06e+02 5.04e+14 -3.8 5.35e-04 18.0 1.00e+00 1.00e+0
0h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
150 -2.9912229e+02 7.06e+02 5.20e+14 -3.8 1.66e-03 17.5 1.00e+00 1.00e+0
0h 1
151 -2.9909106e+02 7.06e+02 5.37e+14 -3.8 6.43e-04 17.9 1.00e+00 1.00e+0
0h 1
152 -2.9907933e+02 7.06e+02 5.54e+14 -3.8 2.49e-04 18.3 1.00e+00 1.00e+0
0h 1
153 -7.2629840e+01 1.76e+02 2.00e+21 -3.8 6.18e+00 17.9 1.00e+00 1.00e+0
0h 1
WARNING: Problem in step computation; switching to emergency mode.
154r-7.2629840e+01 1.76e+02 9.99e+02 2.2 0.00e+00 20.0 0.00e+00 0.00e+0
0R 1
155r-9.3231784e+02 3.75e+02 9.63e+02 2.2 6.90e+04 - 8.81e-02 2.53e-0
3f 1
156r-8.9161799e+02 3.53e+02 4.91e+05 1.5 8.77e+00 6.0 5.54e-02 6.10e-0
2f 1
157r-8.9123056e+02 3.53e+02 6.61e+06 1.5 8.20e+00 9.1 1.16e-01 5.47e-0
4h 1
158r-8.9121712e+02 3.53e+02 5.97e+09 1.5 8.22e+00 10.5 1.67e-01 1.96e-0
5h 1
159r-8.6218884e+02 3.44e+02 7.57e+09 1.5 8.19e+00 10.0 2.01e-01 2.54e-0
2h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
160r-8.6204470e+02 3.44e+02 1.09e+12 1.5 7.97e+00 12.2 3.79e-01 2.44e-0
4h 1
161r-8.6201763e+02 3.44e+02 1.39e+13 1.5 8.01e+00 13.5 2.08e-01 4.15e-0
5h 1
162r-7.4598636e+02 1.84e+02 4.67e+13 1.5 7.92e+00 13.1 3.72e-01 5.85e-0
1h 1
163r-7.4583844e+02 1.84e+02 5.69e+16 1.5 5.62e+00 17.1 6.03e-01 1.20e-0
4h 1
164r-5.2536140e+02 1.64e+02 4.83e+16 1.5 5.43e+00 16.6 1.70e-01 1.29e-0
1h 1
165r-5.2466971e+02 1.64e+02 1.20e+18 1.5 5.11e+00 19.8 2.66e-02 1.13e-0
3h 1
WARNING: Problem in step computation; switching to emergency mode.
166r-5.2466971e+02 1.64e+02 3.63e+17 1.5 5.11e+00 20.0 0.00e+00 0.00e+0
0R 1
WARNING: Problem in step computation; switching to emergency mode.
Cannot call restoration phase at point that is almost feasible for the rest
oration NLP (violation 0.000000e+00).
Abort in line search due to no other fall back.
Step computation in the restoration phase failed.
Number of Iterations....: 166
(scaled) (unscaled)
Objective...............: -5.2466970644132880e+02 -5.2466970644132880e+0
2
Dual infeasibility......: 3.6313679018314899e+17 3.6313679018314899e+1
7
Constraint violation....: 1.6365754660410741e+02 1.6365754660410741e+0
2
Variable bound violation: 0.0000000000000000e+00 0.0000000000000000e+0
0
Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+0
0
Overall NLP error.......: 2.7182234547475359e+03 3.6313679018314899e+1
7
Number of objective function evaluations = 446
Number of objective gradient evaluations = 142
Number of equality constraint evaluations = 446
Number of inequality constraint evaluations = 0
Number of equality constraint Jacobian evaluations = 178
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations = 167
Total seconds in IPOPT = 19.029
EXIT: Restoration Failed!
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 4
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 3
Total number of variables............................: 2
variables with only lower bounds: 0
variables with lower and upper bounds: 0
variables with only upper bounds: 0
Total number of equality constraints.................: 2
Total number of inequality constraints...............: 0
inequality constraints with only lower bounds: 0
inequality constraints with lower and upper bounds: 0
inequality constraints with only upper bounds: 0
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
0 0.0000000e+00 6.09e+02 0.00e+00 -1.0 0.00e+00 - 0.00e+00 0.00e+0
0 0
1 0.0000000e+00 1.90e+02 0.00e+00 -1.0 1.21e+00 - 1.00e+00 1.00e+0
0h 1
2 0.0000000e+00 5.60e+01 0.00e+00 -1.0 8.70e-01 - 1.00e+00 1.00e+0
0h 1
3 0.0000000e+00 1.44e+01 0.00e+00 -1.0 5.61e-01 - 1.00e+00 1.00e+0
0h 1
4 0.0000000e+00 2.57e+00 0.00e+00 -1.0 2.79e-01 - 1.00e+00 1.00e+0
0h 1
5 0.0000000e+00 1.67e-01 0.00e+00 -1.7 7.63e-02 - 1.00e+00 1.00e+0
0h 1
6 0.0000000e+00 9.07e-04 0.00e+00 -2.5 5.71e-03 - 1.00e+00 1.00e+0
0h 1
7 0.0000000e+00 2.71e-08 0.00e+00 -5.7 3.13e-05 - 1.00e+00 1.00e+0
0h 1
Number of Iterations....: 7
(scaled) (unscaled)
Objective...............: 0.0000000000000000e+00 0.0000000000000000e+0
0
Dual infeasibility......: 0.0000000000000000e+00 0.0000000000000000e+0
0
Constraint violation....: 5.4280851813359737e-09 2.7140425906679866e-0
8
Variable bound violation: 0.0000000000000000e+00 0.0000000000000000e+0
0
Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+0
0
Overall NLP error.......: 5.4280851813359737e-09 2.7140425906679866e-0
8
Number of objective function evaluations = 8
Number of objective gradient evaluations = 8
Number of equality constraint evaluations = 8
Number of inequality constraint evaluations = 0
Number of equality constraint Jacobian evaluations = 8
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations = 7
Total seconds in IPOPT = 0.005
EXIT: Optimal Solution Found.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 8844
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 10
Exception of type: TOO_FEW_DOF in file "Interfaces/IpIpoptApplication.cpp"
at line 662:
Exception message: status != TOO_FEW_DEGREES_OF_FREEDOM evaluated false: T
oo few degrees of freedom (rethrown)!
EXIT: Problem has too few degrees of freedom.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 80
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 10
Exception of type: TOO_FEW_DOF in file "Interfaces/IpIpoptApplication.cpp"
at line 662:
Exception message: status != TOO_FEW_DEGREES_OF_FREEDOM evaluated false: T
oo few degrees of freedom (rethrown)!
EXIT: Problem has too few degrees of freedom.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 15
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 15
Total number of variables............................: 5
variables with only lower bounds: 0
variables with lower and upper bounds: 0
variables with only upper bounds: 0
Total number of equality constraints.................: 3
Total number of inequality constraints...............: 0
inequality constraints with only lower bounds: 0
inequality constraints with lower and upper bounds: 0
inequality constraints with only upper bounds: 0
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_p
r ls
0 1.0000000e+00 7.76e+00 9.91e-01 -1.0 0.00e+00 - 0.00e+00 0.00e+0
0 0
1 1.3178035e-01 1.22e+00 5.71e-01 -1.0 7.09e-01 - 1.00e+00 1.00e+0
0h 1
2 8.1454846e-02 6.77e-02 6.41e-02 -1.0 1.13e-01 - 1.00e+00 1.00e+0
0h 1
3 7.8791251e-02 3.95e-04 1.54e-03 -2.5 1.62e-02 - 1.00e+00 1.00e+0
0h 1
4 7.8776829e-02 3.80e-07 4.18e-05 -3.8 7.94e-04 - 1.00e+00 1.00e+0
0h 1
5 7.8776821e-02 8.33e-10 1.63e-06 -5.7 4.97e-05 - 1.00e+00 1.00e+0
0h 1
6 7.8776821e-02 1.26e-13 2.20e-08 -7.0 5.84e-07 - 1.00e+00 1.00e+0
0h 1
Number of Iterations....: 6
(scaled) (unscaled)
Objective...............: 7.8776820987139728e-02 7.8776820987139728e-0
2
Dual infeasibility......: 2.2002492189310274e-08 2.2002492189310274e-0
8
Constraint violation....: 1.2567724638756772e-13 1.2567724638756772e-1
3
Variable bound violation: 0.0000000000000000e+00 0.0000000000000000e+0
0
Complementarity.........: 0.0000000000000000e+00 0.0000000000000000e+0
0
Overall NLP error.......: 2.2002492189310274e-08 2.2002492189310274e-0
8
Number of objective function evaluations = 7
Number of objective gradient evaluations = 7
Number of equality constraint evaluations = 7
Number of inequality constraint evaluations = 0
Number of equality constraint Jacobian evaluations = 7
Number of inequality constraint Jacobian evaluations = 0
Number of Lagrangian Hessian evaluations = 6
Total seconds in IPOPT = 0.005
EXIT: Optimal Solution Found.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 297
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 6
Exception of type: TOO_FEW_DOF in file "Interfaces/IpIpoptApplication.cpp"
at line 662:
Exception message: status != TOO_FEW_DEGREES_OF_FREEDOM evaluated false: T
oo few degrees of freedom (rethrown)!
EXIT: Problem has too few degrees of freedom.
This is Ipopt version 3.14.17, running with linear solver MUMPS 5.8.0.
Number of nonzeros in equality constraint Jacobian...: 40
Number of nonzeros in inequality constraint Jacobian.: 0
Number of nonzeros in Lagrangian Hessian.............: 3
Exception of type: TOO_FEW_DOF in file "Interfaces/IpIpoptApplication.cpp"
at line 662:
Exception message: status != TOO_FEW_DEGREES_OF_FREEDOM evaluated false: T
oo few degrees of freedom (rethrown)!
EXIT: Problem has too few degrees of freedom.
Full results table for equality-constrained problems:
8×5 DataFrame
Row │ problem n_vars secs solver retcode
│ String Int64 Float64 String Symbol
─────┼─────────────────────────────────────────────────
1 │ GAUSS2 8 1.0918 Ipopt Failure
2 │ MSS1 90 19.034 Ipopt Failure
3 │ WAYSEA1NE 2 0.00636697 Ipopt Success
4 │ FBRAIN2 4 0.0045619 Ipopt Failure
5 │ BROWNDENE 4 0.00168896 Ipopt Failure
6 │ HS79 5 0.00636983 Ipopt Success
7 │ GULFNE 3 0.00181985 Ipopt Failure
8 │ JUDGENE 2 0.00160217 Ipopt Failure
Plotted equality-constrained results.Next, we examine the same relationship for problems with inequality-constrained problems.
using DataFrames
all_ineq_unb_problems = CUTEst.select_sif_problems(min_con=1, only_ineq_con=true, only_free_var=true)
# Restrict to a small, easy subset for demonstration/CI
neq_unb_problems = filter(p -> p in ["HS21", "HS35", "HS38", "HS39", "HS41"], all_ineq_unb_problems)
@info "Testing $(length(neq_unb_problems)) inequality-constrained unbounded problems"
# Harmonized analysis block for inequality-constrained unbounded problems
neq_unb_results = run_benchmarks(neq_unb_problems, optimizers; chunk_size=3)
println("Full results table for inequality-constrained problems:")
if nrow(neq_unb_results) > 0
display(neq_unb_results)
else
println("No inequality-constrained results to display. DataFrame is empty.")
end
# Calculate and display success rates for inequality constrained
successful_codes = [:Success, :MaxIters, :MaxTime, :FirstOrderOptimal]
successful_results = filter(row -> row.retcode in successful_codes, neq_unb_results)
total_attempts = nrow(neq_unb_results)
successful_attempts = nrow(successful_results)
success_rate = total_attempts > 0 ? round(successful_attempts / total_attempts * 100, digits=1) : 0
@info "INEQUALITY CONSTRAINED SUCCESS RATE: $(success_rate)% ($(successful_attempts)/$(total_attempts))"
if nrow(neq_unb_results) > 0
try
@df neq_unb_results scatter(:n_vars, :secs,
group = :solver,
xlabel = "n. variables",
ylabel = "secs.",
title = "Time to solution by optimizer and number of vars",
)
println("Plotted inequality-constrained results.")
catch e
println("Plotting failed: ", e)
end
else
println("Warning: inequality-constrained results DataFrame is empty. No data to plot.")
println("Attempted problems:")
println(neq_unb_problems)
endFull results table for inequality-constrained problems:
No inequality-constrained results to display. DataFrame is empty.
Warning: inequality-constrained results DataFrame is empty. No data to plot
.
Attempted problems:
String[]Success Rate Analysis (Equality Constrained)
using DataFrames
total_attempts = nrow(eq_unb_results)
successful_attempts = nrow(successful_results)
success_rate = total_attempts > 0 ? round(successful_attempts / total_attempts * 100, digits=1) : 0
println("SUCCESS RATE ANALYSIS (Equality Constrained):")
println("Total attempts: ", total_attempts)
println("Successful attempts: ", successful_attempts)
println("Success rate: ", success_rate, "%")
println("Return code distribution:")
if total_attempts > 0
for (code, count) in sort(collect(pairs(countmap(eq_unb_results.retcode))), by=x->x[2], rev=true)
println(" ", code, ": ", count, " occurrences")
end
else
println(" No results to analyze")
endSUCCESS RATE ANALYSIS (Equality Constrained):
Total attempts: 8
Successful attempts: 0
Success rate: 0.0%
Return code distribution:
Failure: 6 occurrences
Success: 2 occurrencesSuccess Rate Analysis (Inequality Constrained)
total_attempts_ineq = nrow(neq_unb_results)
successful_attempts_ineq = nrow(successful_results)
success_rate_ineq = total_attempts_ineq > 0 ? round(successful_attempts_ineq / total_attempts_ineq * 100, digits=1) : 0
println("SUCCESS RATE ANALYSIS (Inequality Constrained):")
println("Total attempts: ", total_attempts_ineq)
println("Successful attempts: ", successful_attempts_ineq)
println("Success rate: ", success_rate_ineq, "%")
println("Return code distribution:")
if total_attempts_ineq > 0
for (code, count) in sort(collect(pairs(countmap(neq_unb_results.retcode))), by=x->x[2], rev=true)
println(" ", code, ": ", count, " occurrences")
end
else
println(" No results to analyze")
endSUCCESS RATE ANALYSIS (Inequality Constrained):
Total attempts: 0
Successful attempts: 0
Success rate: 0%
Return code distribution:
No results to analyzeAppendix
These benchmarks are a part of the SciMLBenchmarks.jl repository, found at: https://github.com/SciML/SciMLBenchmarks.jl. For more information on high-performance scientific machine learning, check out the SciML Open Source Software Organization https://sciml.ai.
To locally run this benchmark, do the following commands:
using SciMLBenchmarks
SciMLBenchmarks.weave_file("benchmarks/OptimizationCUTEst","CUTEst_unbounded.jmd")Computer Information:
Julia Version 1.10.10
Commit 95f30e51f41 (2025-06-27 09:51 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 128 × AMD EPYC 7502 32-Core Processor
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-15.0.7 (ORCJIT, znver2)
Threads: 128 default, 0 interactive, 64 GC (on 128 virtual cores)
Environment:
JULIA_CPU_THREADS = 128
JULIA_DEPOT_PATH = /cache/julia-buildkite-plugin/depots/5b300254-1738-4989-ae0a-f4d2d937f953:
Package Information:
Status `/cache/build/exclusive-amdci1-0/julialang/scimlbenchmarks-dot-jl/benchmarks/OptimizationCUTEst/Project.toml`
⌃ [1b53aba6] CUTEst v1.3.2
⌃ [a93c6f00] DataFrames v1.7.0
⌃ [b6b21f68] Ipopt v1.10.6
⌃ [b8f27783] MathOptInterface v1.42.1
⌃ [a4795742] NLPModels v0.21.5
⌅ [7f7a1694] Optimization v4.5.0
⌃ [fd9f6733] OptimizationMOI v0.5.5
⌅ [064b21be] OptimizationNLPModels v0.0.2
⌃ [36348300] OptimizationOptimJL v0.4.3
⌃ [42dfb2eb] OptimizationOptimisers v0.3.8
⌃ [91a5bcdd] Plots v1.40.17
[31c91b34] SciMLBenchmarks v0.1.3
⌃ [2913bbd2] StatsBase v0.34.6
⌃ [f3b207a7] StatsPlots v0.15.7
[de0858da] Printf
[10745b16] Statistics v1.10.0
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated`
Warning The project dependencies or compat requirements have changed since the manifest was last resolved. It is recommended to `Pkg.resolve()` or consider `Pkg.update()` if necessary.And the full manifest:
Status `/cache/build/exclusive-amdci1-0/julialang/scimlbenchmarks-dot-jl/benchmarks/OptimizationCUTEst/Manifest.toml`
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⌃ [4fba245c] ArrayInterface v7.19.0
⌃ [4c555306] ArrayLayouts v1.11.2
[13072b0f] AxisAlgorithms v1.1.0
⌃ [6e4b80f9] BenchmarkTools v1.6.0
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[62783981] BitTwiddlingConvenienceFunctions v0.1.6
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[2e76f6c2] HarfBuzz_jll v8.5.1+0
⌃ [e33a78d0] Hwloc_jll v2.12.1+0
[1d5cc7b8] IntelOpenMP_jll v2025.2.0+0
⌅ [9cc047cb] Ipopt_jll v300.1400.1701+0
⌃ [aacddb02] JpegTurbo_jll v3.1.1+0
[c1c5ebd0] LAME_jll v3.100.3+0
[88015f11] LERC_jll v4.0.1+0
[1d63c593] LLVMOpenMP_jll v18.1.8+0
[dd4b983a] LZO_jll v2.10.3+0
[81d17ec3] L_BFGS_B_jll v3.0.1+0
⌅ [e9f186c6] Libffi_jll v3.4.7+0
[7e76a0d4] Libglvnd_jll v1.7.1+1
[94ce4f54] Libiconv_jll v1.18.0+0
⌃ [4b2f31a3] Libmount_jll v2.41.0+0
⌃ [89763e89] Libtiff_jll v4.7.1+0
⌃ [38a345b3] Libuuid_jll v2.41.0+0
[d00139f3] METIS_jll v5.1.3+0
[856f044c] MKL_jll v2025.2.0+0
⌅ [d7ed1dd3] MUMPS_seq_jll v500.800.0+0
[e7412a2a] Ogg_jll v1.3.6+0
⌅ [656ef2d0] OpenBLAS32_jll v0.3.24+0
⌃ [9bd350c2] OpenSSH_jll v10.0.1+0
⌅ [458c3c95] OpenSSL_jll v3.5.1+0
[efe28fd5] OpenSpecFun_jll v0.5.6+0
⌃ [91d4177d] Opus_jll v1.5.2+0
⌃ [36c8627f] Pango_jll v1.56.3+0
⌅ [30392449] Pixman_jll v0.44.2+0
⌃ [c0090381] Qt6Base_jll v6.8.2+1
[629bc702] Qt6Declarative_jll v6.8.2+1
[ce943373] Qt6ShaderTools_jll v6.8.2+1
⌃ [e99dba38] Qt6Wayland_jll v6.8.2+1
[f50d1b31] Rmath_jll v0.5.1+0
⌅ [54dcf436] SIFDecode_jll v2.6.3+0
⌅ [319450e9] SPRAL_jll v2025.5.20+0
[a44049a8] Vulkan_Loader_jll v1.3.243+0
[a2964d1f] Wayland_jll v1.24.0+0
⌃ [ffd25f8a] XZ_jll v5.8.1+0
[f67eecfb] Xorg_libICE_jll v1.1.2+0
[c834827a] Xorg_libSM_jll v1.2.6+0
[4f6342f7] Xorg_libX11_jll v1.8.12+0
[0c0b7dd1] Xorg_libXau_jll v1.0.13+0
[935fb764] Xorg_libXcursor_jll v1.2.4+0
[a3789734] Xorg_libXdmcp_jll v1.1.6+0
[1082639a] Xorg_libXext_jll v1.3.7+0
⌃ [d091e8ba] Xorg_libXfixes_jll v6.0.1+0
[a51aa0fd] Xorg_libXi_jll v1.8.3+0
[d1454406] Xorg_libXinerama_jll v1.1.6+0
[ec84b674] Xorg_libXrandr_jll v1.5.5+0
[ea2f1a96] Xorg_libXrender_jll v0.9.12+0
[c7cfdc94] Xorg_libxcb_jll v1.17.1+0
[cc61e674] Xorg_libxkbfile_jll v1.1.3+0
⌃ [e920d4aa] Xorg_xcb_util_cursor_jll v0.1.5+0
[12413925] Xorg_xcb_util_image_jll v0.4.1+0
[2def613f] Xorg_xcb_util_jll v0.4.1+0
[975044d2] Xorg_xcb_util_keysyms_jll v0.4.1+0
[0d47668e] Xorg_xcb_util_renderutil_jll v0.3.10+0
[c22f9ab0] Xorg_xcb_util_wm_jll v0.4.2+0
[35661453] Xorg_xkbcomp_jll v1.4.7+0
[33bec58e] Xorg_xkeyboard_config_jll v2.44.0+0
[c5fb5394] Xorg_xtrans_jll v1.6.0+0
[8f1865be] ZeroMQ_jll v4.3.6+0
[3161d3a3] Zstd_jll v1.5.7+1
[35ca27e7] eudev_jll v3.2.14+0
[214eeab7] fzf_jll v0.61.1+0
⌃ [a4ae2306] libaom_jll v3.12.1+0
[0ac62f75] libass_jll v0.17.4+0
[1183f4f0] libdecor_jll v0.2.2+0
[2db6ffa8] libevdev_jll v1.13.4+0
[f638f0a6] libfdk_aac_jll v2.0.4+0
[36db933b] libinput_jll v1.28.1+0
⌃ [b53b4c65] libpng_jll v1.6.50+0
[a9144af2] libsodium_jll v1.0.21+0
[f27f6e37] libvorbis_jll v1.3.8+0
[009596ad] mtdev_jll v1.1.7+0
⌃ [1317d2d5] oneTBB_jll v2022.0.0+0
⌅ [1270edf5] x264_jll v10164.0.1+0
[dfaa095f] x265_jll v4.1.0+0
⌃ [d8fb68d0] xkbcommon_jll v1.9.2+0
[0dad84c5] ArgTools v1.1.1
[56f22d72] Artifacts
[2a0f44e3] Base64
[ade2ca70] Dates
[8ba89e20] Distributed
[f43a241f] Downloads v1.6.0
[7b1f6079] FileWatching
[9fa8497b] Future
[b77e0a4c] InteractiveUtils
[4af54fe1] LazyArtifacts
[b27032c2] LibCURL v0.6.4
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[56ddb016] Logging
[d6f4376e] Markdown
[a63ad114] Mmap
[ca575930] NetworkOptions v1.2.0
[44cfe95a] Pkg v1.10.0
[de0858da] Printf
[9abbd945] Profile
[3fa0cd96] REPL
[9a3f8284] Random
[ea8e919c] SHA v0.7.0
[9e88b42a] Serialization
[1a1011a3] SharedArrays
[6462fe0b] Sockets
[2f01184e] SparseArrays v1.10.0
[10745b16] Statistics v1.10.0
[4607b0f0] SuiteSparse
[fa267f1f] TOML v1.0.3
[a4e569a6] Tar v1.10.0
[8dfed614] Test
[cf7118a7] UUIDs
[4ec0a83e] Unicode
[e66e0078] CompilerSupportLibraries_jll v1.1.1+0
[deac9b47] LibCURL_jll v8.4.0+0
[e37daf67] LibGit2_jll v1.6.4+0
[29816b5a] LibSSH2_jll v1.11.0+1
[c8ffd9c3] MbedTLS_jll v2.28.2+1
[14a3606d] MozillaCACerts_jll v2023.1.10
[4536629a] OpenBLAS_jll v0.3.23+4
[05823500] OpenLibm_jll v0.8.5+0
[efcefdf7] PCRE2_jll v10.42.0+1
[bea87d4a] SuiteSparse_jll v7.2.1+1
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.52.0+1
[3f19e933] p7zip_jll v17.4.0+2
Info Packages marked with ⌃ and ⌅ have new versions available. Those with ⌃ may be upgradable, but those with ⌅ are restricted by compatibility constraints from upgrading. To see why use `status --outdated -m`
Warning The project dependencies or compat requirements have changed since the manifest was last resolved. It is recommended to `Pkg.resolve()` or consider `Pkg.update()` if necessary.