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stringclasses
3 values
season
stringclasses
5 values
campaign
stringclasses
4 values
strategy
stringclasses
6 values
revenue
float64
48.5k
80.5k
gross_margin_pct
float64
38.7
44.9
stockout_rate_pct
float64
0
0.85
waste_rate_pct
float64
3.17
9.32
choice_coverage_pct
float64
46.7
50
price_stability_score
float64
88
100
decision_regret_pct
float64
88.3
90.6
solve_time_sec
float64
0.02
0.05
grocery_retail
holiday
flash_sale
stable_pricing_policy
78,312.42
41.79
0
9.32
50
98.27
89.72
0.026
grocery_retail
summer
baseline
pyomo_joint_optimizer
80,545.83
43.4
0
9.32
50
93.46
89.42
0.019
consumer_electronics
winter
loyalty_push
choice_assortment_opt
48,516.02
41.25
0.85
6.29
50
90.53
88.67
0.015
consumer_electronics
holiday
clearance
thompson_bandit
50,025.11
42.76
0.73
6.3
50
92.04
88.32
0.017
fashion_apparel
spring
baseline
cvxpy_relaxation
65,644.81
38.72
0.65
3.17
46.67
100
90.55
0.028
fashion_apparel
fall
flash_sale
robust_pricing
73,031.94
44.93
0.59
3.19
46.67
88.03
89.49
0.048
grocery_retail
winter
clearance
stable_pricing_policy
78,312.42
41.79
0
9.32
50
98.27
89.72
0.027

PriceForge Sample Scenarios

Synthetic retail catalog scenarios for integrated pricing, assortment, and inventory optimization benchmarks.

Each JSON file contains a full optimization result with pricing decisions, assortment selection, replenishment plan, demand forecasts, and SimPy simulation output.

See manifest.json for the sample index and eval_results.json for MLflow-compatible benchmark metrics.

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