Vehicle Routing Problem Instances for Comparing Sub-terminal Operational Models
Description
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