Aria AI Operations Research Portfolio
Collection
Enterprise OR, optimization, and decomposition demos by Aria AI • 95 items • Updated
benchmark_count int64 | leaderboard dict | metrics dict |
|---|---|---|
60 | {
"instances": 30,
"solver_count": 8,
"selector_top1_accuracy": 0.5,
"avg_par10": 0.127,
"avg_oracle_regret": 23.14,
"leaderboard": [
{
"solver_id": "cp_sat",
"label": "OR-Tools CP-SAT",
"wins": 15,
"win_rate": 0.5,
"feasible_rate": 1,
"avg_gap_pct": 24.34,
"avg... | {
"selector_top1_accuracy": 0.5,
"avg_par10": 0.127,
"avg_oracle_regret": 23.14
} |
SolverPort Solver Performance Dataset
Solver benchmark results across 8 solvers and 10 optimization problem families.
Metrics per Run
- Runtime (seconds)
- Optimality gap (%)
- Feasibility status
- Time to first feasible solution
- Best bound and gap improvement rate
- Search speed
- PAR10 penalty score
- Oracle regret vs best solver
Solvers Profiled
CP-SAT, HiGHS, CBC, SCIP, GLPK, Gurobi, MiniZinc, ALNS
Files
{instance_id}_performance.json— full benchmark run with all solver resultseval_results.json— aggregate leaderboard and selector accuracymanifest.json— dataset index
Usage
from huggingface_hub import hf_hub_download
import json
path = hf_hub_download(
repo_id="alirezaaminzadeh/solverport-solver-performance",
filename="eval_results.json",
repo_type="dataset",
)
results = json.load(open(path))
print(results["metrics"]["selector_top1_accuracy"])
License
Apache 2.0
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