此示例展示了如何使用 loadDemands 和 loadLimits 在路线优化 API 请求中管理车辆运力限制。
如需查看完整的概念性概览，请参阅负载需求和限制关键概念文档。
示例请求
以下示例演示了一个场景，其中一辆有载重限制的车辆必须运送三批不同重量的货物。
此示例请求包含以下与负载相关的参数：
shipments[0]，负载需求为 50weightKg（amount）。shipments[1]，负载需求为 10weightKg，amount。shipments[2]，负载需求为 80weightKg（即amount）。vehicles[0]，负载限制为 100weightKg。maxLoad
查看包含负载需求和限制的示例请求
{ "populatePolylines": false, "populateTransitionPolylines": false, "model": { "globalStartTime": "2023-01-13T16:00:00Z", "globalEndTime": "2023-01-14T16:00:00Z", "shipments": [ { "deliveries": [ { "arrivalLocation": { "latitude": 37.789456, "longitude": -122.390192 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 100.0, "loadDemands": { "weightKg": { "amount": "50" } } }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.789116, "longitude": -122.395080 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 15.0, "loadDemands": { "weightKg": { "amount": "10" } } }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.795242, "longitude": -122.399347 }, "duration": "250s" } ], "pickups": [ { "arrivalLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "duration": "150s" } ], "penaltyCost": 50.0, "loadDemands": { "weightKg": { "amount": "80" } } } ], "vehicles": [ { "endLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "startLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "costPerHour": 40.0, "costPerKilometer": 10.0, "loadLimits": { "weightKg": { "maxLoad": "100" } } } ] } }
示例响应
响应会显示车辆的优化路线。由于所有货件的总负载超过了车辆的容量，因此优化器会创建一系列取货和送货顺序，以确保不违反 loadLimits。
查看对包含负载需求和限制的请求的响应
{ "routes": [ { "vehicleStartTime": "2023-01-13T16:00:00Z", "vehicleEndTime": "2023-01-13T16:43:27Z", "visits": [ { "isPickup": true, "startTime": "2023-01-13T16:00:00Z", "detour": "0s", "loadDemands": { "weightKg": { "amount": "50" } } }, { "shipmentIndex": 1, "isPickup": true, "startTime": "2023-01-13T16:02:30Z", "detour": "150s", "loadDemands": { "weightKg": { "amount": "10" } } }, { "startTime": "2023-01-13T16:08:55Z", "detour": "150s", "loadDemands": { "weightKg": { "amount": "-50" } } }, { "shipmentIndex": 1, "startTime": "2023-01-13T16:16:37Z", "detour": "343s", "loadDemands": { "weightKg": { "amount": "-10" } } }, { "shipmentIndex": 2, "isPickup": true, "startTime": "2023-01-13T16:27:07Z", "detour": "1627s", "loadDemands": { "weightKg": { "amount": "80" } } }, { "shipmentIndex": 2, "startTime": "2023-01-13T16:36:26Z", "detour": "0s", "loadDemands": { "weightKg": { "amount": "-80" } } } ], "transitions": [ { "travelDuration": "0s", "waitDuration": "0s", "totalDuration": "0s", "startTime": "2023-01-13T16:00:00Z", "vehicleLoads": { "weightKg": {} } }, { "travelDuration": "0s", "waitDuration": "0s", "totalDuration": "0s", "startTime": "2023-01-13T16:02:30Z", "vehicleLoads": { "weightKg": { "amount": "50" } } }, { "travelDuration": "235s", "travelDistanceMeters": 795, "waitDuration": "0s", "totalDuration": "235s", "startTime": "2023-01-13T16:05:00Z", "vehicleLoads": { "weightKg": { "amount": "60" } } }, { "travelDuration": "212s", "travelDistanceMeters": 791, "waitDuration": "0s", "totalDuration": "212s", "startTime": "2023-01-13T16:13:05Z", "vehicleLoads": { "weightKg": { "amount": "10" } } }, { "travelDuration": "380s", "travelDistanceMeters": 1190, "waitDuration": "0s", "totalDuration": "380s", "startTime": "2023-01-13T16:20:47Z", "vehicleLoads": { "weightKg": {} } }, { "travelDuration": "409s", "travelDistanceMeters": 1371, "waitDuration": "0s", "totalDuration": "409s", "startTime": "2023-01-13T16:29:37Z", "vehicleLoads": { "weightKg": { "amount": "80" } } }, { "travelDuration": "171s", "travelDistanceMeters": 665, "waitDuration": "0s", "totalDuration": "171s", "startTime": "2023-01-13T16:40:36Z", "vehicleLoads": { "weightKg": {} } } ], "metrics": { "performedShipmentCount": 3, "travelDuration": "1407s", "waitDuration": "0s", "delayDuration": "0s", "breakDuration": "0s", "visitDuration": "1200s", "totalDuration": "2607s", "travelDistanceMeters": 4812, "maxLoads": { "weightKg": { "amount": "80" } } }, "routeCosts": { "model.vehicles.cost_per_kilometer": 48.12, "model.vehicles.cost_per_hour": 28.966666666666665 }, "routeTotalCost": 77.086666666666659 } ], "metrics": { "aggregatedRouteMetrics": { "performedShipmentCount": 3, "travelDuration": "1407s", "waitDuration": "0s", "delayDuration": "0s", "breakDuration": "0s", "visitDuration": "1200s", "totalDuration": "2607s", "travelDistanceMeters": 4812, "maxLoads": { "weightKg": { "amount": "80" } } }, "usedVehicleCount": 1, "earliestVehicleStartTime": "2023-01-13T16:00:00Z", "latestVehicleEndTime": "2023-01-13T16:43:27Z", "totalCost": 77.086666666666659, "costs": { "model.vehicles.cost_per_hour": 28.966666666666665, "model.vehicles.cost_per_kilometer": 48.12 } } }
由于这三批货物的总 loadDemands（50 + 10 + 80 = 140）超过了车辆的 loadLimits（100），因此车辆无法一次性取走所有货物。由于 shipment[0] 和 shipment[2] 的总重量超过了车辆的载重限制，因此优化器只会考虑 shipment[0] 和 shipment[2] 不会同时装载在车辆中的路线。
路线的 visits 不得超过车辆的载重限制：
shipment[0]已自提shipment[1]已自提shipment[0]已送达shipment[1]已送达shipment[2]已自提shipment[2]已送达
车辆的载重在整个路线中都会发生变化，您可以在 transitions 数组中观察到这一点。例如，transitions[2] 显示了车辆在装载 60 个 weightKg 的货物（50 + 10）后，又装载了另外 60 个 weightKg 的货物。
metrics 中的 maxLoads 属性显示，路线中任何时间点所载的最大负荷为 80 weightKg，这证实了该解决方案成功将负荷保持在车辆的 100 weightKg 限制范围内。
软性负载限制
以下示例展示了如何使用软载重限制来优化包含多辆车的路线。该解决方案将货物分摊到两辆车上，以避免因超出车辆的软载重限制而产生的费用罚款。
示例请求
此请求现在包含 3 个仅送货的货件和 2 辆具有相同 loadLimits 和 softMaxLoad 的车辆。
此示例的关键参数如下：
- 这三批货物的总
loadDemands为 140weightKg（50- 60 + 30）。
- 有两款车辆的
softMaxLoad为“100”weightKg，costPerUnitAboveSoftMax为 5.0。
查看包含软加载限制的请求示例
{ "populatePolylines": false, "populateTransitionPolylines": false, "model": { "globalStartTime": "2023-01-13T16:00:00Z", "globalEndTime": "2023-01-14T16:00:00Z", "shipments": [ { "deliveries": [ { "arrivalLocation": { "latitude": 37.789456, "longitude": -122.390192 }, "duration": "250s" } ], "loadDemands": { "weightKg": { "amount": "50" } } }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.789116, "longitude": -122.395080 }, "duration": "250s" } ], "loadDemands": { "weightKg": { "amount": "60" } } }, { "deliveries": [ { "arrivalLocation": { "latitude": 37.795242, "longitude": -122.399347 }, "duration": "250s" } ], "loadDemands": { "weightKg": { "amount": "30" } } } ], "vehicles": [ { "endLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "startLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "costPerHour": 40.0, "costPerKilometer": 10.0, "loadLimits": { "weightKg": { "maxLoad": "150", "softMaxLoad": "100", "costPerUnitAboveSoftMax": 5.0 } } }, { "endLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "startLocation": { "latitude": 37.794465, "longitude": -122.394839 }, "costPerHour": 40.0, "costPerKilometer": 10.0, "loadLimits": { "weightKg": { "maxLoad": "150", "softMaxLoad": "100", "costPerUnitAboveSoftMax": 5.0 } } } ] } }
示例响应
响应现在包含两条路线，每辆车各一条。优化器确定，与使用一辆车并产生软限制罚款相比，使用两辆车更具成本效益。
查看对具有软负载限制的请求的响应
{ "routes": [ { "vehicleStartTime": "2023-01-13T16:00:00Z", "vehicleEndTime": "2023-01-13T16:13:31Z", "visits": [ { "startTime": "2023-01-13T16:03:53Z", "detour": "0s", "loadDemands": { "weightKg": { "amount": "-50" } } } ], "transitions": [ { "travelDuration": "233s", "travelDistanceMeters": 794, "waitDuration": "0s", "totalDuration": "233s", "startTime": "2023-01-13T16:00:00Z", "vehicleLoads": { "weightKg": { "amount": "50" } } }, { "travelDuration": "328s", "travelDistanceMeters": 1188, "waitDuration": "0s", "totalDuration": "328s", "startTime": "2023-01-13T16:08:03Z", "vehicleLoads": { "weightKg": {} } } ], "metrics": { "performedShipmentCount": 1, "travelDuration": "561s", "visitDuration": "250s", "totalDuration": "811s", "travelDistanceMeters": 1982, "maxLoads": { "weightKg": { "amount": "50" } } }, "routeCosts": { "model.vehicles.cost_per_kilometer": 19.82, "model.vehicles.cost_per_hour": 9.01 }, "routeTotalCost": 28.83 }, { "vehicleIndex": 1, "vehicleStartTime": "2023-01-13T16:00:00Z", "vehicleEndTime": "2023-01-13T16:21:43Z", "visits": [ { "shipmentIndex": 1, "startTime": "2023-01-13T16:05:54Z", "detour": "0s", "loadDemands": { "weightKg": { "amount": "-60" } } }, { "shipmentIndex": 2, "startTime": "2023-01-13T16:13:52Z", "detour": "473s", "loadDemands": { "weightKg": { "amount": "-30" } } } ], "transitions": [ { "travelDuration": "354s", "travelDistanceMeters": 1196, "waitDuration": "0s", "totalDuration": "354s", "startTime": "2023-01-13T16:00:00Z", "vehicleLoads": { "weightKg": { "amount": "90" } } }, { "travelDuration": "228s", "travelDistanceMeters": 808, "waitDuration": "0s", "totalDuration": "228s", "startTime": "2023-01-13T16:10:04Z", "vehicleLoads": { "weightKg": { "amount": "30" } } }, { "travelDuration": "221s", "travelDistanceMeters": 655, "waitDuration": "0s", "totalDuration": "221s", "startTime": "2023-01-13T16:18:02Z", "vehicleLoads": { "weightKg": {} } } ], "metrics": { "performedShipmentCount": 2, "travelDuration": "803s", "visitDuration": "500s", "totalDuration": "1303s", "travelDistanceMeters": 2659, "maxLoads": { "weightKg": { "amount": "90" } } }, "routeCosts": { "model.vehicles.cost_per_kilometer": 26.59, "model.vehicles.cost_per_hour": 14.48 }, "routeTotalCost": 41.07 } ], "metrics": { "aggregatedRouteMetrics": { "performedShipmentCount": 3, "travelDuration": "1364s", "visitDuration": "750s", "totalDuration": "2114s", "travelDistanceMeters": 4641, "maxLoads": { "weightKg": { "amount": "90" } } }, "usedVehicleCount": 2, "earliestVehicleStartTime": "2023-01-13T16:00:00Z", "latestVehicleEndTime": "2023-01-13T16:21:43Z", "totalCost": 69.90, "costs": { "model.vehicles.cost_per_kilometer": 46.41, "model.vehicles.cost_per_hour": 23.49 } } }
以下字段显示了优化器如何将货物分配到两辆车上，以使每辆车的载重不超过 100 weightKg 的软限制。
- 第一个路线（
vehicleIndex：0）处理 50 个weightKg货件。其maxLoads为“50”，低于软性限制。 - 第二条路线（
vehicleIndex：1）处理 60 和 30weightKg的货件。其maxLoads为“90”，也低于软性限制。 - 由于两辆车均未违反其软限制，因此两条路线的
routeCosts均未显示costPerUnitAboveSoftMax惩罚。