Datasets:
Modalities:
Text
Formats:
json
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< 1K
Tags:
retail
inventory-optimization
predict-then-optimize
chronos-2
operations-research
stochastic-programming
License:
File size: 1,561 Bytes
aade9b0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 | {
"instance_id": "holiday_surge_s123",
"scenario_id": "holiday_surge",
"seed": 123,
"oracle_cost": 32296.56,
"forecast_decoupling": false,
"insight": "For this scenario, deterministic_p50 aligns forecast accuracy and decision cost optimality.",
"policies": [
{
"policy": "naive_ma",
"mae": 9.599,
"rmse": 12.821,
"total_cost": 40219.91,
"stockout_cost": 20810.29,
"holding_cost": 531.37,
"waste_cost": 4594.88,
"service_level": 0.89115,
"decision_regret": 7923.350000000002,
"runtime_sec": 0.011
},
{
"policy": "deterministic_p50",
"mae": 7.884,
"rmse": 9.636,
"total_cost": 37352.64,
"stockout_cost": 2.58,
"holding_cost": 522.3,
"waste_cost": 20690.4,
"service_level": 1.0,
"decision_regret": 5056.079999999998,
"runtime_sec": 0.0112
},
{
"policy": "quantile_stochastic",
"mae": 8.001,
"rmse": 9.74,
"total_cost": 49488.74,
"stockout_cost": 0.0,
"holding_cost": 1063.65,
"waste_cost": 32069.38,
"service_level": 1.0,
"decision_regret": 17192.179999999997,
"runtime_sec": 0.0412
},
{
"policy": "quantile_robust",
"mae": 8.113,
"rmse": 9.873,
"total_cost": 67092.12,
"stockout_cost": 0.0,
"holding_cost": 1281.56,
"waste_cost": 49176.03,
"service_level": 1.0,
"decision_regret": 34795.56,
"runtime_sec": 0.0409
}
]
} |