AI-generated Key Takeaways
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Route Optimization's cost model, defined by various cost parameters, guides the optimization process by enabling trade-offs between factors like time, distance, and shipment completion.
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Cost parameters, expressed in dimensionless units, are assigned to
VehicleandShipmentproperties, allowing users to prioritize route characteristics and shipment importance. -
Shipmentpenalty costs influence whether a shipment is included in a route; if the cost to complete a shipment exceeds its penalty cost, it may be skipped. -
The
OptimizeToursResponsemessage provides cost breakdowns, includingmetrics.costsandrouteCosts, offering insights into the cost efficiency of the generated routes. -
Soft constraints, such as
LoadLimitandTimeWindow, introduce cost penalties when violated, allowing for flexibility while still encouraging adherence to limits.
This example shows how to use cost parameters to get a cost-effective route.
For a complete conceptual overview, see the Cost model key concept document.
Example request
The following example demonstrates a scenario where one vehicle must deliver
three shipments. The vehicle has associated costs for time and distance, and
each shipment has a penaltyCost that is incurred if the shipment is
skipped.
This example request contains the following cost-related parameters:
shipments[0]with apenaltyCostof 100.0.shipments[1]with apenaltyCostof 5.0.shipments[2]with apenaltyCostof 50.0.vehicles[0]with acostPerHourof 40.0 and acostPerKilometerof 10.0.
See an example request with costs
{ "model": { "globalStartTime": "2023-01-13T16:00:00-08:00", "globalEndTime": "2023-01-14T16:00:00-08:00", "shipments": [ { "deliveries": [ { "arrivalLocation": { "latitude": 37.789456, "longitude": -122.390192 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 100.0 }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.789116, "longitude": -122.395080 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 5.0 }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.795242, "longitude": -122.399347 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 50.0 } ], "vehicles": [ { "endLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "startLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "costPerHour": 40.0, "costPerKilometer": 10.0 } ] } }
Example response
The response shows that the optimizer creates a route that performs two of the
three shipments. The third shipment is skipped because its penaltyCost is
lower than the calculated vehicle costs for pickup and delivery.
See a response to the example request with costs
{ "routes": [ { "vehicleStartTime": "2023-01-14T00:00:00Z", "vehicleEndTime": "2023-01-14T00:28:22Z", "visits": [ { "isPickup": true, "startTime": "2023-01-14T00:00:00Z", "detour": "0s" }, { "shipmentIndex": 2, "isPickup": true, "startTime": "2023-01-14T00:02:30Z", "detour": "150s" }, { "startTime": "2023-01-14T00:08:55Z", "detour": "150s" }, { "shipmentIndex": 2, "startTime": "2023-01-14T00:21:21Z", "detour": "572s" } ], "transitions": [ { "travelDuration": "0s", "waitDuration": "0s", "totalDuration": "0s", "startTime": "2023-01-14T00:00:00Z" }, { "travelDuration": "0s", "waitDuration": "0s", "totalDuration": "0s", "startTime": "2023-01-14T00:02:30Z" }, { "travelDuration": "235s", "travelDistanceMeters": 795, "waitDuration": "0s", "totalDuration": "235s", "startTime": "2023-01-14T00:05:00Z" }, { "travelDuration": "496s", "travelDistanceMeters": 1893, "waitDuration": "0s", "totalDuration": "496s", "startTime": "2023-01-14T00:13:05Z" }, { "travelDuration": "171s", "travelDistanceMeters": 665, "waitDuration": "0s", "totalDuration": "171s", "startTime": "2023-01-14T00:25:31Z" } ], "metrics": { "performedShipmentCount": 2, "travelDuration": "902s", "waitDuration": "0s", "delayDuration": "0s", "breakDuration": "0s", "visitDuration": "800s", "totalDuration": "1702s", "travelDistanceMeters": 3353 }, "routeCosts": { "model.vehicles.cost_per_kilometer": 33.53, "model.vehicles.cost_per_hour": 18.911111111111111 }, "routeTotalCost": 52.441111111111113 } ], "skippedShipments": [ { "index": 1 } ], "metrics": { "aggregatedRouteMetrics": { "performedShipmentCount": 2, "travelDuration": "902s", "waitDuration": "0s", "delayDuration": "0s", "breakDuration": "0s", "visitDuration": "800s", "totalDuration": "1702s", "travelDistanceMeters": 3353 }, "usedVehicleCount": 1, "earliestVehicleStartTime": "2023-01-14T00:00:00Z", "latestVehicleEndTime": "2023-01-14T00:28:22Z", "totalCost": 57.441111111111113, "costs": { "model.vehicles.cost_per_kilometer": 33.53, "model.vehicles.cost_per_hour": 18.911111111111111, "model.shipments.penalty_cost": 5 } } }
The following fields show how the costs are calculated in the response:
routeCostsbreaks down the operational costs for a specific route, which in this case are:model.vehicles.cost_per_kilometer: 33.53.model.vehicles.cost_per_hour: 18.91.
- The
routeTotalCost(52.44) is the sum of the costs listed inrouteCosts. - At the top level of the response, the
costsobject summarizes every cost incurred in the solution. This includes the operational costs from all vehicle routes plus any penalties, such as themodel.shipments.penalty_cost(5.0) for the skipped shipment. - The final
totalCost(57.44) represents the grand total for the solution, which is the sum of therouteTotalCostfrom all vehicles and all penalty costs. In this case, it is 52.44 + 5.0.