| { |
| "num_facilities": "<int> Number of candidate facility locations.", |
| "num_customers": "<int> Number of customers whose demand must be satisfied.", |
| "num_scenarios": "<int> Number of demand scenarios considered.", |
| "capacity_factor": "<float> Ratio of total facility capacity to total expected demand, controlling how tight capacity is.", |
| "variance_level": "<str> Level of demand variability across scenarios ('normal' or 'high').", |
| "facilities": [ |
| { |
| "id": "<int> Zero-based index identifying the facility.", |
| "opening_cost": "<float> Fixed cost incurred if this facility is opened.", |
| "capacity": "<float> Maximum total units this facility can ship across all customers in any scenario.", |
| "location_x": "<float> X-coordinate of the facility location, used to compute transportation costs.", |
| "location_y": "<float> Y-coordinate of the facility location, used to compute transportation costs." |
| } |
| ], |
| "customers": [ |
| { |
| "id": "<int> Zero-based index identifying the customer.", |
| "deterministic_demand": "<float> Expected (mean) demand of this customer.", |
| "demand_std_fraction": "<float> Ratio of demand standard deviation to mean demand for this customer.", |
| "location_x": "<float> X-coordinate of the customer location, used to compute transportation costs.", |
| "location_y": "<float> Y-coordinate of the customer location, used to compute transportation costs." |
| } |
| ], |
| "transportation_costs": "<list[list[float]], shape [num_facilities][num_customers]> Per-unit cost of shipping from each facility to each customer, equal to the Euclidean distance between them.", |
| "scenarios": [ |
| { |
| "id": "<int> Zero-based index identifying the scenario.", |
| "probability": "<float> Probability of this scenario occurring.", |
| "demands": "<list[float], length num_customers> Realized demand of each customer under this scenario." |
| } |
| ] |
| } |
|
|
