Aria AI Operations Research Portfolio
Collection
Enterprise OR, optimization, and decomposition demos by Aria AI • 136 items • Updated
benchmark_count int64 | total_runs int64 | leaderboard dict | budget_leaderboards dict | research dict | metrics dict |
|---|---|---|---|---|---|
96 | 384 | {
"instances": 96,
"selector_top1_accuracy": 1,
"family_win_counts": {
"classical": 58,
"metaheuristic": 3,
"neural": 35
},
"leaderboard": [
{
"solver_id": "ortools",
"label": "OR-Tools",
"family": "classical",
"wins": 28,
"feasible_rate": 0.3333,
"avg_gap_p... | {
"10": {
"instances": 96,
"selector_top1_accuracy": 1,
"family_win_counts": {
"classical": 64,
"metaheuristic": 0,
"neural": 32
},
"leaderboard": [
{
"solver_id": "ortools",
"label": "OR-Tools",
"family": "classical",
"wins": 41,
"fe... | {
"research_question": "Where does neural combinatorial optimization really win?",
"summary": [
"Small instances: exact/classical solvers achieve the best solution quality.",
"Large instances: neural solvers reach feasible solutions earlier under tight budgets.",
"Research hypotheses supported: 2/3."
... | {
"selector_top1_accuracy": 1,
"family_win_counts": {
"classical": 58,
"metaheuristic": 3,
"neural": 35
}
} |
frontierco-solver-performance
Solver performance benchmark dataset produced by the FrontierCO Solver Arena.
Source
Built on profiles aligned with CO-Bench/FrontierCO.
Contents
| Field | Description |
|---|---|
instance_id |
Unique instance identifier |
problem_type |
One of 8 CO problems |
size |
small / medium / large |
difficulty |
easy / hard |
time_budget_sec |
10 / 30 / 60 / 300 |
solver_id |
One of 13 solvers |
optimality_gap_pct |
Gap to known optimum |
runtime_sec |
Wall-clock seconds |
feasible |
Feasibility flag |
time_to_first_feasible_sec |
Time to first feasible solution |
memory_mb |
Peak memory estimate |
scalability_score |
Scalability index |
Use Cases
- Algorithm selection model training
- Solver portfolio analysis
- Neural vs classical CO research
- Time-budget sensitivity studies
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