本指南演示了路线优化解决方案中提供的车辆数量如何因请求参数而异。
Route Optimization API 不仅会优化运输完成顺序，还会将这些运输分配给车辆，以便在您管理的约束条件下优化费用。
在第一个示例中，车辆数量与运输数量相符，并且所有车辆都具有相同的费用和位置属性。每辆车都有每小时运营费用和每公里行驶费用，这有助于最大限度地缩短行驶时间和距离。您可能希望为多个车辆分配运输任务，但示例响应会根据指定的费用模型参数显示费用最低的解决方案。
查看包含多个车辆的请求示例
{
"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": 50.0,
"costPerKilometer": 10.0
},
{
"endLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"startLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"costPerHour": 50.0,
"costPerKilometer": 10.0
},
{
"endLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"startLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"costPerHour": 50.0,
"costPerKilometer": 10.0
}
]
}
}
查看针对包含多辆车辆的请求的响应
{
"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": 23.638888888888889
},
"routeTotalCost": 57.168888888888887
},
{
"vehicleIndex": 1
},
{
"vehicleIndex": 2
}
],
"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": 62.168888888888887,
"costs": {
"model.vehicles.cost_per_hour": 23.638888888888889,
"model.shipments.penalty_cost": 5,
"model.vehicles.cost_per_kilometer": 33.53
}
}
}
求解器会将所有运输分配给一辆车辆，即使有充足的车辆可用，也会跳过一笔运输。这是因为运营额外的车辆的成本过高，而且由于违规处罚费用较低，任何车辆都无法以经济实惠的方式完成漏送的配送。尽管车辆载重量足够，但一辆车可以以最具成本效益的方式完成所有分配的运输任务。请求中的车辆未设置 usedIfRouteIsEmpty 属性（如需了解详情，请参阅 Vehicle 消息文档 [REST、gRPC]），因此如果未使用，则不会产生费用。
更改费用参数，以优先考虑总体路线更短的解决方案，而不是单个车辆路线更短的解决方案，会导致更多车辆参与该解决方案。下一个示例请求会将 Vehicle.costPerHour 替换为全局 ShipmentModel.globalDurationCostPerHour，优先考虑总运行时间短的解决方案（对于任何给定车辆）。shipment[1] 的惩罚费用也会增加，以降低被跳过的可能性。
查看使用 globalDurationCostPerHour 的示例请求
{
"model": {
"globalStartTime": "2023-01-13T16:00:00-08:00",
"globalEndTime": "2023-01-14T16:00:00-08:00",
"globalDurationCostPerHour": 150.0,
"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": 75.0
},
{
"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
},
"costPerKilometer": 10.0
},
{
"endLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"startLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"costPerKilometer": 10.0
},
{
"endLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"startLocation": {
"latitude": 37.794465,
"longitude": -122.394839
},
"costPerKilometer": 10.0
}
]
}
}
结果表明，使用全局每小时费用参数会导致使用所有三辆车辆，而不是仅使用一辆车辆。
查看使用 globalDurationCostPerHour 对请求的响应
{
"routes": [
{
"vehicleStartTime": "2023-01-14T00:00:00Z",
"vehicleEndTime": "2023-01-14T00:16:20Z",
"visits": [
{
"shipmentIndex": 2,
"isPickup": true,
"startTime": "2023-01-14T00:00:00Z",
"detour": "0s"
},
{
"shipmentIndex": 2,
"startTime": "2023-01-14T00:09:19Z",
"detour": "0s"
}
],
"transitions": [
{
"travelDuration": "0s",
"waitDuration": "0s",
"totalDuration": "0s",
"startTime": "2023-01-14T00:00:00Z"
},
{
"travelDuration": "409s",
"travelDistanceMeters": 1371,
"waitDuration": "0s",
"totalDuration": "409s",
"startTime": "2023-01-14T00:02:30Z"
},
{
"travelDuration": "171s",
"travelDistanceMeters": 665,
"waitDuration": "0s",
"totalDuration": "171s",
"startTime": "2023-01-14T00:13:29Z"
}
],
"metrics": {
"performedShipmentCount": 1,
"travelDuration": "580s",
"waitDuration": "0s",
"delayDuration": "0s",
"breakDuration": "0s",
"visitDuration": "400s",
"totalDuration": "980s",
"travelDistanceMeters": 2036
},
"routeCosts": {
"model.vehicles.cost_per_kilometer": 20.36
},
"routeTotalCost": 20.36
},
{
"vehicleIndex": 1,
"vehicleStartTime": "2023-01-14T00:00:00Z",
"vehicleEndTime": "2023-01-14T00:18:54Z",
"visits": [
{
"shipmentIndex": 1,
"isPickup": true,
"startTime": "2023-01-14T00:00:00Z",
"detour": "0s"
},
{
"shipmentIndex": 1,
"startTime": "2023-01-14T00:08:24Z",
"detour": "0s"
}
],
"transitions": [
{
"travelDuration": "0s",
"waitDuration": "0s",
"totalDuration": "0s",
"startTime": "2023-01-14T00:00:00Z"
},
{
"travelDuration": "354s",
"travelDistanceMeters": 1192,
"waitDuration": "0s",
"totalDuration": "354s",
"startTime": "2023-01-14T00:02:30Z"
},
{
"travelDuration": "380s",
"travelDistanceMeters": 1190,
"waitDuration": "0s",
"totalDuration": "380s",
"startTime": "2023-01-14T00:12:34Z"
}
],
"metrics": {
"performedShipmentCount": 1,
"travelDuration": "734s",
"waitDuration": "0s",
"delayDuration": "0s",
"breakDuration": "0s",
"visitDuration": "400s",
"totalDuration": "1134s",
"travelDistanceMeters": 2382
},
"routeCosts": {
"model.vehicles.cost_per_kilometer": 23.82
},
"routeTotalCost": 23.82
},
{
"vehicleIndex": 2,
"vehicleStartTime": "2023-01-14T00:00:00Z",
"vehicleEndTime": "2023-01-14T00:16:14Z",
"visits": [
{
"isPickup": true,
"startTime": "2023-01-14T00:00:00Z",
"detour": "0s"
},
{
"startTime": "2023-01-14T00:06:25Z",
"detour": "0s"
}
],
"transitions": [
{
"travelDuration": "0s",
"waitDuration": "0s",
"totalDuration": "0s",
"startTime": "2023-01-14T00:00:00Z"
},
{
"travelDuration": "235s",
"travelDistanceMeters": 795,
"waitDuration": "0s",
"totalDuration": "235s",
"startTime": "2023-01-14T00:02:30Z"
},
{
"travelDuration": "339s",
"travelDistanceMeters": 1276,
"waitDuration": "0s",
"totalDuration": "339s",
"startTime": "2023-01-14T00:10:35Z"
}
],
"metrics": {
"performedShipmentCount": 1,
"travelDuration": "574s",
"waitDuration": "0s",
"delayDuration": "0s",
"breakDuration": "0s",
"visitDuration": "400s",
"totalDuration": "974s",
"travelDistanceMeters": 2071
},
"routeCosts": {
"model.vehicles.cost_per_kilometer": 20.71
},
"routeTotalCost": 20.71
}
],
"metrics": {
"aggregatedRouteMetrics": {
"performedShipmentCount": 3,
"travelDuration": "1888s",
"waitDuration": "0s",
"delayDuration": "0s",
"breakDuration": "0s",
"visitDuration": "1200s",
"totalDuration": "3088s",
"travelDistanceMeters": 6489
},
"usedVehicleCount": 3,
"earliestVehicleStartTime": "2023-01-14T00:00:00Z",
"latestVehicleEndTime": "2023-01-14T00:18:54Z",
"totalCost": 112.14,
"costs": {
"model.vehicles.cost_per_kilometer": 64.89,
"model.global_duration_cost_per_hour": 47.25
}
}
}
在此响应中，所有三辆车辆均处于使用状态（每个 metrics.usedVehicleCount），每辆车辆都分配了一份运输任务来完成。由于起始位置、终点位置和 costPerKilometer 相同，因此这三辆车实际上是可以互换的，因此分配给哪辆车的运输无关紧要。
globalDurationCostPerHour 会导致优化器找到总体更短的解决方案：earliestVehicleStartTime 和 latestVehicleEndTime 之间的差异仅为 18 分钟 54 秒，而上一个响应中的差异为 28 分钟 22 秒。不过，metrics.costs.model.vehicles.cost_per_kilometer 有所增加，反映了三辆二手车的总行驶里程增加。这展示了利用成本模型进行权衡的一种方式：
- 增加总时间成本：提高车辆利用率以尽可能缩短总完成时间，但会增加车辆行驶距离和运输时间。
- 增加车辆时间成本：降低车辆利用率和运输时间，但总体解决方案的用时会延长。
请注意，本例中的 globalDurationCostPerHour 值 150.0 是上例中各车辆 costPerHour 值 50.0 的三倍。此全局费用值实际上假定所有三辆车都将同时运行，但在实际设置中，此类假设可能并不符合实际情况，事实上可能会对结果质量产生负面影响。
如费用模型参数中所述，所有费用参数均采用相同的无量纲单位表示，但可能具有完全不同的含义。通常，费用模型参数值应尽可能基于现实情况，因为此示例中所述的人工费用可能会导致 API 针对与您的意图不符的目标进行优化。