Path: blob/main/tests/tools/drt/drtOrtools/waiting_time2/output.tools
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Simulation parameters:
end: 600.0
interval: 30
time_limit: 10
cost_type: CostType.DISTANCE
drf: 3.0
waiting_time: 80.0
fix_allocation: True
timestep: 0.0
Reservations waiting: ['0', '1']
Taxis empty: ('v0',)
Solve CPDP
Start creating the model.
dp reservations: ['0', '1']
do reservations: []
Reservation 0 starts at edge B0C0
Reservation 1 starts at edge C2C1
Reservation 0 ends at edge C1C2
Reservation 1 ends at edge C0B0
Reservation 0 has direct route costs 485
Reservation 1 has direct route costs 480
Penalty factor is 2000
Start solving the problem.
Register distance callback.
Create time dimension.
Add distance constraints...
Add pickup and delivery constraints...
pickup/dropoff nodes: 1/2
allow to reject new reservation 0
pickup/dropoff nodes: 3/4
allow to reject new reservation 1
Add direct route factor constraints...
reservation 0: direct route cost 485 and (hard) max cost 1455
reservation 1: direct route cost 480 and (hard) max cost 1440
Add dropoff constraints...
Add "no re-allocation" constraints...
Add capacity constraints...
Add time windows constraints...
hard time window for node 1: [1, 600]
hard time window for node 2: [1, 600]
hard time window for node 3: [1, 600]
hard time window for node 4: [1, 600]
hard time window for node 5: [1, 600]
Add waiting time constraints...
reservation 0 has a maximum (hard) pickup time at 80
reservation 1 has a maximum (hard) pickup time at 80
## Done
Set solution heuristic...
Start solving the problem.
Objective: 401073
Route for vehicle 0:
5 (L: 0, C: 0, T: (1,38))
-> 1 (L: 1, C: 588, T: (43,80))
-> 2 (L: 0, C: 1073, T: (142,600))
-> 0 (L: 0, C: 1073, T: (142,600))
Costs of the route: 1073
Total cost of the routes: 1073
Start interpreting the solution for SUMO.
Dispatching v0 with ['0', '0']
Costs for v0: 1073
timestep: 30.0
Reservations waiting: ['1']
Reservations being picked up: ['0']
Taxis picking up: ('v0',)
Solve CPDP
Start creating the model.
dp reservations: ['0', '1']
do reservations: []
Reservation 0 starts at edge B0C0
Reservation 1 starts at edge C2C1
Reservation 0 ends at edge C1C2
Reservation 1 ends at edge C0B0
Reservation 0 has direct route costs 485
Reservation 1 has direct route costs 480
Penalty factor is 900
Start solving the problem.
Register distance callback.
Create time dimension.
Add distance constraints...
Add pickup and delivery constraints...
pickup/dropoff nodes: 1/2
pickup/dropoff nodes: 3/4
allow to reject new reservation 1
Add direct route factor constraints...
reservation 0: direct route cost 485 and (soft) max cost 1455
reservation 1: direct route cost 480 and (hard) max cost 1440
Add dropoff constraints...
Add "no re-allocation" constraints...
reservation 0 in veh id=0
Add capacity constraints...
Add time windows constraints...
soft time window for node 1: [30, 600]
soft time window for node 2: [30, 600]
hard time window for node 3: [30, 600]
hard time window for node 4: [30, 600]
hard time window for node 5: [30, 600]
Add waiting time constraints...
reservation 0 has a maximum (soft) pickup time at 80
reservation 1 has a maximum (hard) pickup time at 80
## Done
Set solution heuristic...
Start solving the problem.
Initial solution:
veh 0: [1, 2]
Objective: 180771
Route for vehicle 0:
5 (L: 0, C: 0, T: (30,30))
-> 1 (L: 1, C: 286, T: (51,51))
-> 2 (L: 0, C: 771, T: (150,150))
-> 0 (L: 0, C: 771, T: (150,150))
Costs of the route: 771
Total cost of the routes: 771
Start interpreting the solution for SUMO.
Dispatching v0 with ['0', '0']
Costs for v0: 771
timestep: 60.0
Reservations waiting: ['1']
Reservations en route: ['0']
Taxis occupied: ('v0',)
Solve CPDP
Start creating the model.
dp reservations: ['1']
do reservations: ['0']
Reservation 1 starts at edge C2C1
Reservation 1 ends at edge C0B0
Drop-off of reservation 0 at edge C1C2
Reservation 0 has direct route costs 485
Reservation 1 has direct route costs 480
Penalty factor is 900
Start solving the problem.
Register distance callback.
Create time dimension.
Add distance constraints...
Add pickup and delivery constraints...
pickup/dropoff nodes: 2/3
allow to reject new reservation 1
Add direct route factor constraints...
reservation 1: direct route cost 480 and (hard) max cost 1440
reservation 0: direct route cost 485 and (soft) max cost 1455, already used costs 324
Add dropoff constraints...
reservation 0 in veh v0(0), droppoff node: 1
Add "no re-allocation" constraints...
Add capacity constraints...
Add time windows constraints...
soft time window for node 1: [60, 600]
hard time window for node 2: [60, 600]
hard time window for node 3: [60, 600]
hard time window for node 4: [60, 600]
Add waiting time constraints...
reservation 1 has a maximum (hard) pickup time at 80
## Done
Set solution heuristic...
Start solving the problem.
Initial solution:
veh 0: [1]
Objective: 180186
Route for vehicle 0:
4 (L: 1, C: 0, T: (60,60))
-> 1 (L: 0, C: 186, T: (133,133))
-> 0 (L: 0, C: 186, T: (133,133))
Costs of the route: 186
Total cost of the routes: 186
Start interpreting the solution for SUMO.
Dispatching v0 with ['0']
Costs for v0: 186
timestep: 90.0
Reservations waiting: ['1']
Reservations en route: ['0']
Taxis occupied: ('v0',)
Solve CPDP
Start creating the model.
Reservations rejected: ['1']
dp reservations: []
do reservations: ['0']
Drop-off of reservation 0 at edge C1C2
Reservation 0 has direct route costs 485
Penalty factor is 90
Start solving the problem.
Register distance callback.
Create time dimension.
Add distance constraints...
Add pickup and delivery constraints...
Add direct route factor constraints...
reservation 0: direct route cost 485 and (soft) max cost 1455, already used costs 480
Add dropoff constraints...
reservation 0 in veh v0(0), droppoff node: 1
Add "no re-allocation" constraints...
Add capacity constraints...
Add time windows constraints...
soft time window for node 1: [90, 600]
hard time window for node 2: [90, 600]
Add waiting time constraints...
## Done
Set solution heuristic...
Start solving the problem.
Initial solution:
veh 0: [1]
Objective: 86
Route for vehicle 0:
2 (L: 1, C: 0, T: (90,90))
-> 1 (L: 0, C: 86, T: (96,96))
-> 0 (L: 0, C: 86, T: (96,96))
Costs of the route: 86
Total cost of the routes: 86
Start interpreting the solution for SUMO.
Dispatching v0 with ['0']
Costs for v0: 86
timestep: 120.0
Reservations en route: ['0']
Taxis occupied: ('v0',)
timestep: 150.0
Reservations en route: ['0']
Taxis occupied: ('v0',)
timestep: 180.0
Taxis empty: ('v0',)
timestep: 210.0
Taxis empty: ('v0',)
timestep: 240.0
Taxis empty: ('v0',)
timestep: 270.0
Taxis empty: ('v0',)
timestep: 300.0
Taxis empty: ('v0',)
timestep: 330.0
Taxis empty: ('v0',)
timestep: 360.0
Taxis empty: ('v0',)
timestep: 390.0
Taxis empty: ('v0',)
timestep: 420.0
Taxis empty: ('v0',)
timestep: 450.0
Taxis empty: ('v0',)
timestep: 480.0
Taxis empty: ('v0',)
timestep: 510.0
Taxis empty: ('v0',)
timestep: 540.0
Taxis empty: ('v0',)
timestep: 570.0
Taxis empty: ('v0',)
timestep: 600.0
Taxis empty: ('v0',)