Vehicle Routing Problem Instances for Comparing Sub-terminal Operational Models

Vehicle Routing Problem Instances for Comparing Sub-terminal Operational Models

Data Abstract:

The problem instances consist of the following scenarios:
- Case-studied delivery sub-terminals: terminal_B (end-chute numbers 1-2 and 3-5 separately), terminal_S
- Differences in the number of delivery truck stops: -0%, -20%, -40%, -60%, -80%
- Differences in delivery service time in seconds (average service time per parcel): 0 (-120s), -15 (-105s), -30 (-90s), -45 (-75s), -60 (-60s)
- Number of trucks per each end-chute: 1 each, 2 each, 3 each, 4 each, 5 each
- Delivery sub-terminal operational model: AS-IS, TO-BE

For each scenario (instance):
- Demand.csv: For each delivery location, index, number of parcels to be delivered (multiplied by 100), service time required, and round number
- Vehicle.csv: For each delivery vehicle, vehicle name (id), number of parcels to be loaded (multiplied by 100), and round number
- Matrix_Distance.csv: NxN distance matrix
- Matrix_Time.csv: NxN time matrix
(*Number of deliveries is multiplied by 100 in order to keep the number integer)

The vehicle routing problem solution is provided in _Solution.csv for each scenario (instance):
- Total distance: Summed travel distance of the delivery vehicles
- Total time: Summed travel time and service time of the delivery vehicles
- Total time travel: Summed travel time of the delivery vehicles
- Total time service: Summed service time of the delivery vehicles
- Round: Round number for the vehicle route
- VehId: Vehicle name (id) for the vehicle route
- VehStops: Visiting node indices for the vehicle route
- VehBoxes: Number of parcels for the vehicle route
- VehDistance: Travel distance for the vehicle route
- VehTime: Travel time and service time for the vehicle route
- VehTimeTravel: Travel time for the vehicle route
- VehTimeService: Service time for the vehicle route