{
  "instance_id": "baseline_s123",
  "scenario_id": "baseline",
  "seed": 123,
  "oracle_cost": 32984.4,
  "forecast_decoupling": false,
  "insight": "For this scenario, deterministic_p50 aligns forecast accuracy and decision cost optimality.",
  "policies": [
    {
      "policy": "naive_ma",
      "mae": 9.05,
      "rmse": 11.918,
      "total_cost": 39516.26,
      "stockout_cost": 20061.51,
      "holding_cost": 514.67,
      "waste_cost": 4534.53,
      "service_level": 0.8957999999999999,
      "decision_regret": 6531.860000000001,
      "runtime_sec": 0.0112
    },
    {
      "policy": "deterministic_p50",
      "mae": 6.723,
      "rmse": 8.101,
      "total_cost": 35026.04,
      "stockout_cost": 15.86,
      "holding_cost": 518.22,
      "waste_cost": 18625.78,
      "service_level": 0.9999,
      "decision_regret": 2041.6399999999994,
      "runtime_sec": 0.0115
    },
    {
      "policy": "quantile_stochastic",
      "mae": 6.823,
      "rmse": 8.228,
      "total_cost": 46877.67,
      "stockout_cost": 0.0,
      "holding_cost": 1040.34,
      "waste_cost": 29556.31,
      "service_level": 1.0,
      "decision_regret": 13893.269999999997,
      "runtime_sec": 0.0405
    },
    {
      "policy": "quantile_robust",
      "mae": 6.924,
      "rmse": 8.336,
      "total_cost": 64065.52,
      "stockout_cost": 0.0,
      "holding_cost": 1253.05,
      "waste_cost": 46230.68,
      "service_level": 1.0,
      "decision_regret": 31081.119999999995,
      "runtime_sec": 0.0407
    }
  ]
}