OptimizeToursRequest
消息(REST、gRPC)包含许多与费用相关的属性。这些费用参数共同表示请求的费用模型。费用模型可捕获许多请求的高级优化目标,例如:
- 优先选择较快的
Vehicle
路线,而不是较短的路线,反之亦然 - 确定交付
Shipment
的成本是否值得Shipment
完成的价值 - 仅在这样做具有成本效益时,才在时间范围内执行取货和送货
查看包含费用的示例请求
{ "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 } ] } }
Vehicle
费用属性
Vehicle
消息(REST、gRPC)具有以下几个费用属性:
Vehicle.cost_per_hour
:表示每小时的车辆运营成本,包括运输、等待、访问和休息时间。Vehicle.cost_per_kilometer
:表示车辆每行驶一公里的费用。Vehicle.cost_per_traveled_hour
:表示车辆仅在行驶过程中的运营成本,不包括等待、访问和休息时间。
借助这些费用参数,优化器可以权衡时间与行驶距离。优化后的路线产生的费用在响应消息中显示为 metrics.costs
:
随着 costPerHour
的增加,优化器会尝试寻找可能不是最短路线的更快路线。在此示例中,最快路线恰好是最短路线,因此更改费用参数几乎没有影响。
Shipment
费用属性
Shipment
消息(REST、gRPC)还具有多个费用参数:
Shipment.penalty_cost
表示跳过发货所产生的费用。不设置配送的penalty_cost
参数会使配送成为强制性,这意味着只有在无法在指定限制条件下完成配送时,才会跳过该配送。Shipment.VisitRequest.cost
表示特定取件或送货的费用,主要用于在单个货件的多个取件或送货选项之间实现费用权衡。
Shipment
费用形参使用与 Vehicle
费用形参相同的无量纲单位。如果完成 Shipment
所产生的费用超过其惩罚费用,则任何 Vehicle
的路线中都不会包含 Shipment
,而是会在响应消息的 skipped_shipments
列表中显示。
ShipmentModel
费用属性
ShipmentModel
消息(REST、gRPC)包含一个费用属性 globalDurationCostPerHour
。此费用是根据所有车辆完成其 ShipmentRoute
所需的总时间产生的。增加 globalDurationCostPerHour
会优先考虑尽早完成所有配送。
路线优化响应费用属性
OptimizeToursResponse
消息(REST、gRPC)具有表示完成 ShipmentRoute
的过程中产生的费用的费用属性。metrics.costs
和 metrics.totalCost
属性表示响应中所有路线产生的费用单位数。每个 routes
条目都具有 routeCosts
和 routeTotalCosts
属性,用于表示相应特定路线的费用。
查看包含费用的示例请求的响应
{ "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": 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 } } }
在示例响应中,顶级 metrics.costs
为:
{
"metrics": {
...
"costs": {
"model.vehicles.cost_per_hour": 18.911111111111111,
"model.vehicles.cost_per_kilometer": 33.53,
"model.shipments.penalty_cost": 5
}
}
}
model.shipments.penalty_cost
值表示因跳过配送而产生的费用。skippedShipments
属性列出了哪些配送被跳过。
在此示例中,仅跳过示例请求中的 model.shipments[1]
。model.shipments[1]
的惩罚费用为 5 个单位,与示例响应中的 model.shipments.penalty_cost
键的总费用相符。与 Vehicle
的 40.0 costPerHour
和 10.0 costPerKilometer
相比,该货件的 penaltyCost
较低,因此跳过该货件比完成该货件更具成本效益。
高级主题:费用和软约束
多个 OptimizeToursRequest
消息(REST、gRPC)属性表示软约束,即无法满足时会产生费用的约束。
例如,车辆 LoadLimit
(REST、gRPC)限制具有 softMaxLoad
和 costPerUnitAboveSoftMax
属性。这些费用加起来与超出 softMaxLoad
的负载单位成正比,因此只有在从费用角度来看有意义时,才能超出限额。
同样,TimeWindow
约束(REST、gRPC)具有 soft_start_time
和 soft_end_time
属性,以及相应的 cost_per_hour_before_soft_start_time
和 cost_per_hour_after_soft_end_time
,这些属性会根据受限事件相对于 TimeWindow
的发生时间(早或晚)而产生。
与所有成本模型参数一样,软约束成本以与其他成本参数相同的无量纲单位表示。
负载需求和限制中详细介绍了 LoadLimit
限制。取货和送货时间窗口限制中详细介绍了 TimeWindow
限制。