Datasets:

alirezaaminzadeh
/

orderpromise-sample-network

Products: SKU, cost, price, substitutes, production lead time
Warehouses: inventory levels, capacity, handling costs
Network edges: lead times, shipping costs, capacities
Orders: multi-line requests with customer tier and delivery window

benchmark_count int64	avg_fill_rate float64	avg_profit_uplift_pct float64	metrics list	benchmarks list
4	1	106.8	[ "profit_uplift", "late_delivery_reduction", "order_fill_rate", "decision_regret" ]	[ { "industry": "ecommerce", "order_id": "ORD-80316", "recommended": "express", "fill_rate": 1, "profit_uplift": 7.7, "solve_time": 0.484 }, { "industry": "industrial", "order_id": "ORD-11244", "recommended": "express", "fill_rate": 1, "profit_uplift": 6.1, "solve_t...

OrderPromise Sample Network Dataset

Synthetic supply-chain network data for order promising and fulfillment optimization demos.

File	Description
`manifest.json`	Dataset metadata and schema
`sample_ecommerce.json`	E-commerce order + 3-warehouse network
`sample_industrial.json`	Industrial equipment with production lines
`sample_pharma.json`	Pharmaceutical distribution scenario
`eval_results.json`	Benchmark metrics across industries

import json
with open("sample_ecommerce.json") as f:
    instance = json.load(f)

MIT