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Fix: syntax errors and undefined references in CUTEst benchmarks #1448

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Fix: syntax errors and undefined references in CUTEst benchmarks #1448

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5 changes: 0 additions & 5 deletions benchmarks/OptimizationCUTEst/CUTEst_quadratic.jmd
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Original file line number Diff line number Diff line change
Expand Up @@ -109,11 +109,6 @@ function run_benchmarks(problems, optimizers; chunk_size=1)
return DataFrame(problem = problem, n_vars = n_vars, secs = secs, solver = solver, retcode = retcode)
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)
end
```

# Benchmarks
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2 changes: 1 addition & 1 deletion benchmarks/OptimizationCUTEst/CUTEst_unbounded.jmd
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Expand Up @@ -194,7 +194,7 @@ neq_unb_problems = filter(p -> p in ["HS21", "HS35", "HS38", "HS39", "HS41"], al


# Harmonized analysis block for inequality-constrained unbounded problems
neq_unb_results = run_unbounded_benchmarks(neq_unb_problems, optimizers; chunk_size=3)
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)
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25 changes: 0 additions & 25 deletions benchmarks/OptimizationCUTEst/CUTEst_unconstrained.jmd
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Expand Up @@ -13,31 +13,6 @@ CUTEst, the Constrained and Unconstrained Testing Environment, is a collection o
CUTEst contains 286 unconstrained problems. We will compare how the optimizers behave in
terms of the time to solution with respect to the number of variables.

total_attempts = nrow(unc_results)
successful_attempts = nrow(successful_results)
success_rate = total_attempts > 0 ? round(successful_attempts / total_attempts * 100, digits=1) : 0

println("SUCCESS RATE ANALYSIS:")
println("Total attempts: ", total_attempts)
println("Successful attempts: ", successful_attempts)
println("Success rate: ", success_rate, "%")

# Show distribution of return codes
println("Return code distribution:")
if total_attempts > 0
for (code, count) in sort(collect(pairs(countmap(unc_results.retcode))), by=x->x[2], rev=true)
println(" ", code, ": ", count, " occurrences")
end
else
println(" No results to analyze")
end

@df unc_results scatter(:n_vars, :secs,
group = :solver,
xlabel = "n. variables",
ylabel = "secs.",
title = "Time to solution by optimizer and number of vars",
)

```julia
using Optimization
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