Aria AI Operations Research Portfolio
Collection
Enterprise OR, optimization, and decomposition demos by Aria AI • 7 items • Updated
benchmark_count int64 | selector_top1_accuracy float64 | winners_by_problem dict |
|---|---|---|
49 | 0.143 | {
"supply_chain": "progressive_hedging",
"multi_factory": "progressive_hedging",
"large_routing": "column_generation",
"multi_stage_scheduling": "column_generation",
"energy_planning": "progressive_hedging",
"fleet_allocation": "progressive_hedging",
"network_design": "progressive_hedging"
} |
DecompBench Benchmark Dataset
Pre-computed decomposition benchmark results for Large-Scale Optimization Decomposition Lab by Aria AI.
Contents
manifest.json— dataset metadataeval_results.json— selector accuracy summaryinstances/— synthetic problem instances (JSON)
Problem Families
Supply chain, multi-factory production, large routing, multi-stage scheduling, energy planning, fleet allocation, network design.
Methods
Monolithic MIP, Benders, Dantzig-Wolfe, Column Generation, Lagrangian Relaxation, Progressive Hedging, ADMM.
Metrics
Time to first solution, time to target gap, iterations, columns/cuts, memory, lower bound quality, optimality gap, scalability.
Space
https://huggingface.co/spaces/alirezaaminzadeh/large-scale-optimization-decomposition-lab
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