取貨和運送時間限制

OptimizeToursRequest 會在下列項目中套用限制:

  • Shipments,影響運送方式
  • 車輛,影響車輛路線的計算方式
  • 全球皆受影響,包括車輛和出貨。

本指南著重於重要的運送限制:時間窗

時間範圍是一種限制,您可以在 OptimizeToursRequest 訊息 (RESTgRPC) 中提供這項限制,以便指定運送活動的時間限制。這類限制會影響運送作業的時間、方式,以及運送車輛的分配。在這些限制下,最佳化工具會優先選擇最能滿足運送時間限制的車輛。

運送限制:時間區間

您可以在 Shipment.VisitRequest 訊息中指定取件或送達時間,如下所示:

  • 在訊息中使用 timeWindows 屬性 (RESTgRPC)
  • TimeWindow 訊息中指定開始和結束時間 (RESTgRPC)。

含有時間範圍限制的示例要求

以下範例說明三個不同的出貨作業,每個出貨作業都有各自的運送時間範圍。為求簡單明瞭,本例只會在 deliveries 上設定時間窗,但時間窗也可以套用至接送地點。您可以指定多個時間視窗,但本範例只會在每個提交 VisitRequest 時使用一個。

查看含有時間回溯期的申請範例

{
  "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",
            "timeWindows": [
              {
                "startTime": "2023-01-13T18:00:00Z",
                "endTime": "2023-01-13T19:00:00Z"
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 100.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.789116,
              "longitude": -122.395080
            },
            "duration": "250s",
            "timeWindows": [
              {
                "startTime": "2023-01-13T18:00:00Z",
                "endTime": "2023-01-13T18:30:00Z"
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 20.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.795242,
              "longitude": -122.399347
            },
            "duration": "250s",
            "timeWindows": [
              {
                "startTime": "2023-01-13T17:30:00Z",
                "endTime": "2023-01-13T18:00:00Z"
              }
            ]
          }
        ],
        "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
      }
    ]
  }
}
    

含有時間範圍限制的回應範例

在範例回應中,車輛的開始和結束時間分別為 17:35:50 和 18:17:24。這些時間反映了最佳化器盡量縮短操作車輛所需的時間,並在滿足所有時間區間限制的情況下,將車輛指定為 costPerHour。使用 17:35:50 做為開始時間,車輛就不需要在到訪地點等待,直到到訪時間範圍開始。這會在回應中顯示為零 waitDuration 值。

查看範例要求的回應,並瞭解時間視窗

{
  "routes": [
    {
      "vehicleStartTime": "2023-01-13T17:35:50Z",
      "vehicleEndTime": "2023-01-13T18:17:24Z",
      "visits": [
        {
          "isPickup": true,
          "startTime": "2023-01-13T17:35:50Z",
          "detour": "0s"
        },
        {
          "shipmentIndex": 1,
          "isPickup": true,
          "startTime": "2023-01-13T17:38:20Z",
          "detour": "150s"
        },
        {
          "shipmentIndex": 2,
          "isPickup": true,
          "startTime": "2023-01-13T17:40:50Z",
          "detour": "300s"
        },
        {
          "shipmentIndex": 2,
          "startTime": "2023-01-13T17:50:09Z",
          "detour": "0s"
        },
        {
          "shipmentIndex": 1,
          "startTime": "2023-01-13T18:00:00Z",
          "detour": "796s"
        },
        {
          "startTime": "2023-01-13T18:07:35Z",
          "detour": "1520s"
        }
      ],
      "transitions": [
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:35:50Z"
        },
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:38:20Z"
        },
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:40:50Z"
        },
        {
          "travelDuration": "409s",
          "travelDistanceMeters": 1371,
          "waitDuration": "0s",
          "totalDuration": "409s",
          "startTime": "2023-01-13T17:43:20Z"
        },
        {
          "travelDuration": "341s",
          "travelDistanceMeters": 1312,
          "waitDuration": "0s",
          "totalDuration": "341s",
          "startTime": "2023-01-13T17:54:19Z"
        },
        {
          "travelDuration": "205s",
          "travelDistanceMeters": 636,
          "waitDuration": "0s",
          "totalDuration": "205s",
          "startTime": "2023-01-13T18:04:10Z"
        },
        {
          "travelDuration": "339s",
          "travelDistanceMeters": 1276,
          "waitDuration": "0s",
          "totalDuration": "339s",
          "startTime": "2023-01-13T18:11:45Z"
        }
      ],
      "metrics": {
        "performedShipmentCount": 3,
        "travelDuration": "1294s",
        "waitDuration": "0s",
        "delayDuration": "0s",
        "breakDuration": "0s",
        "visitDuration": "1200s",
        "totalDuration": "2494s",
        "travelDistanceMeters": 4595
      },
      "routeCosts": {
        "model.vehicles.cost_per_hour": 27.711111111111112,
        "model.vehicles.cost_per_kilometer": 45.95
      },
      "routeTotalCost": 73.661111111111111
    }
  ],
  "metrics": {
    "aggregatedRouteMetrics": {
      "performedShipmentCount": 3,
      "travelDuration": "1294s",
      "waitDuration": "0s",
      "delayDuration": "0s",
      "breakDuration": "0s",
      "visitDuration": "1200s",
      "totalDuration": "2494s",
      "travelDistanceMeters": 4595
    },
    "usedVehicleCount": 1,
    "earliestVehicleStartTime": "2023-01-13T17:35:50Z",
    "latestVehicleEndTime": "2023-01-13T18:17:24Z",
    "totalCost": 73.661111111111111,
    "costs": {
      "model.vehicles.cost_per_hour": 27.711111111111112,
      "model.vehicles.cost_per_kilometer": 45.95
    }
  }
}
    

時間窗口會排序車輛的 visits,讓最早的時間窗口先送達。

  1. shipments[2] 已於 17:50 送達
  2. shipments[1] 已於 18:00 送達
  3. shipments[0] 已於 18:07 送達

示例要求會指定硬性時間範圍限制,要求在這些範圍內完成提交作業。如果在任何時間範圍內完成出貨的 VisitRequests 不可行或不划算,最佳化器就會略過該出貨。如果運送作業含有 penaltyCost,最佳化工具會將其加進回應 metrics 中回報的費用。否則,OptimizeToursResponse 訊息 (RESTgRPC) 的 skippedMandatoryShipmentCount 屬性會增加。

如果您將 shipment[1] 的時間區間往後推幾小時 (從 18:00 推到 21:00),結果就會有所不同,如以下範例所示。

請參閱無法滿足時間範圍要求的示例

{
  "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",
            "timeWindows": [
              {
                "startTime": "2023-01-13T18:00:00Z",
                "endTime": "2023-01-13T19:00:00Z"
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 100.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.789116,
              "longitude": -122.395080
            },
            "duration": "250s",
            "timeWindows": [
              {
                "startTime": "2023-01-13T21:00:00Z",
                "endTime": "2023-01-13T21:30:00Z"
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 20.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.795242,
              "longitude": -122.399347
            },
            "duration": "250s",
            "timeWindows": [
              {
                "startTime": "2023-01-13T17:30:00Z",
                "endTime": "2023-01-13T18:00:00Z"
              }
            ]
          }
        ],
        "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
      }
    ]
  }
}
    

查看針對含有時間窗口的第二個範例要求的回應,其中顯示了跳過的出貨

{
  "routes": [
    {
      "vehicleStartTime": "2023-01-13T17:37:49Z",
      "vehicleEndTime": "2023-01-13T18:09:49Z",
      "visits": [
        {
          "isPickup": true,
          "startTime": "2023-01-13T17:37:49Z",
          "detour": "0s"
        },
        {
          "shipmentIndex": 2,
          "isPickup": true,
          "startTime": "2023-01-13T17:40:19Z",
          "detour": "150s"
        },
        {
          "shipmentIndex": 2,
          "startTime": "2023-01-13T17:49:38Z",
          "detour": "0s"
        },
        {
          "startTime": "2023-01-13T18:00:00Z",
          "detour": "946s"
        }
      ],
      "transitions": [
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:37:49Z"
        },
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:40:19Z"
        },
        {
          "travelDuration": "409s",
          "travelDistanceMeters": 1371,
          "waitDuration": "0s",
          "totalDuration": "409s",
          "startTime": "2023-01-13T17:42:49Z"
        },
        {
          "travelDuration": "372s",
          "travelDistanceMeters": 1348,
          "waitDuration": "0s",
          "totalDuration": "372s",
          "startTime": "2023-01-13T17:53:48Z"
        },
        {
          "travelDuration": "339s",
          "travelDistanceMeters": 1276,
          "waitDuration": "0s",
          "totalDuration": "339s",
          "startTime": "2023-01-13T18:04:10Z"
        }
      ],
      "metrics": {
        "performedShipmentCount": 2,
        "travelDuration": "1120s",
        "waitDuration": "0s",
        "delayDuration": "0s",
        "breakDuration": "0s",
        "visitDuration": "800s",
        "totalDuration": "1920s",
        "travelDistanceMeters": 3995
      },
      "routeCosts": {
        "model.vehicles.cost_per_kilometer": 39.95,
        "model.vehicles.cost_per_hour": 21.333333333333332
      },
      "routeTotalCost": 61.283333333333331
    }
  ],
  "skippedShipments": [
    {
      "index": 1
    }
  ],
  "metrics": {
    "aggregatedRouteMetrics": {
      "performedShipmentCount": 2,
      "travelDuration": "1120s",
      "waitDuration": "0s",
      "delayDuration": "0s",
      "breakDuration": "0s",
      "visitDuration": "800s",
      "totalDuration": "1920s",
      "travelDistanceMeters": 3995
    },
    "usedVehicleCount": 1,
    "earliestVehicleStartTime": "2023-01-13T17:37:49Z",
    "latestVehicleEndTime": "2023-01-13T18:09:49Z",
    "totalCost": 81.283333333333331,
    "costs": {
      "model.shipments.penalty_cost": 20,
      "model.vehicles.cost_per_hour": 21.333333333333332,
      "model.vehicles.cost_per_kilometer": 39.95
    }
  }
}
    

在本例中,後續時間範圍導致 shipment[1] 遭到略過,因為在指定時間範圍內完成運送所需的額外車輛運作時間,超過了運送的罰款成本。shipment[1] 的罰則費用會顯示在 metrics.costs 中,而其索引會顯示在 skippedShipments 中。

軟性時間範圍限制

成本模式參數中所述,時間視窗可做為軟性限制條件套用。軟性限制與硬性限制的差異如下:

  • 硬性限制條件:無法違反,且最佳化工具不會提供違反限制條件的解決方案,即使這代表會略過某次出貨也一樣。
  • 軟性限制條件:可能會違反限制條件,也就是說最佳化器可能會提供違反軟性限制條件的解決方案。不過,最佳化工具也會對任何違規行為套用費用。您可以在時間範圍中提供這項費用做為額外資源,通常是活動發生時間範圍前後每小時的費用。

您可以分別使用 softStartTimesoftEndTime 而非 startTimeendTime,並設定 costPerHourBeforeSoftStartTimecostPerHourAfterSoftEndTime,藉此讓時間視窗變得較為柔軟。

如果取件或送達服務「應」在指定的時間範圍內進行,但並非絕對必須在該時間範圍內,請使用軟性時間範圍限制。您可以同時使用硬性和軟性時間範圍限制來表達業務目標。例如:

  • 固定時間範圍:表示客戶的營業時間,例如上午 9 點到下午 5 點。
  • 軟性時間範圍:表示與傳送給客戶的通知相符的運送或取貨時間範圍,例如上午 9 點到下午 1 點。

在本範例中,先前因為時間視窗開始得太晚而略過的運送作業,其開始時間限制已放寬。其他運送訂單的時間窗口也已延後。

查看含有硬性和軟性時間範圍的示例要求

{
  "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",
            "timeWindows": [
              {
                "startTime": "2023-01-13T18:00:00Z",
                "softEndTime": "2023-01-13T19:00:00Z",
                "costPerHourAfterSoftEndTime": 2.0
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 100.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.789116,
              "longitude": -122.395080
            },
            "duration": "250s",
            "timeWindows": [
              {
                "softStartTime": "2023-01-13T21:00:00Z",
                "endTime": "2023-01-13T21:30:00Z",
                "costPerHourBeforeSoftStartTime": 2.0
              }
            ]
          }
        ],
        "pickups": [
          {
            "arrivalLocation": {
              "latitude": 37.794465,
              "longitude": -122.394839
            },
            "duration": "150s"
          }
        ],
        "penaltyCost": 20.0
      },
      {
        "deliveries": [
          {
            "arrivalLocation": {
              "latitude": 37.795242,
              "longitude": -122.399347
            },
            "duration": "250s",
            "timeWindows": [
              {
                "startTime": "2023-01-13T17:30:00Z",
                "softEndTime": "2023-01-13T18:00:00Z",
                "costPerHourAfterSoftEndTime": 2.0
              }
            ]
          }
        ],
        "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
      }
    ]
  }
}
    

查看對含有硬性和軟性時間間隔的示例要求的回應

{
  "routes": [
    {
      "vehicleStartTime": "2023-01-13T17:48:35Z",
      "vehicleEndTime": "2023-01-13T18:24:28Z",
      "visits": [
        {
          "isPickup": true,
          "startTime": "2023-01-13T17:48:35Z",
          "detour": "0s"
        },
        {
          "shipmentIndex": 1,
          "isPickup": true,
          "startTime": "2023-01-13T17:51:05Z",
          "detour": "150s"
        },
        {
          "shipmentIndex": 2,
          "isPickup": true,
          "startTime": "2023-01-13T17:53:35Z",
          "detour": "300s"
        },
        {
          "startTime": "2023-01-13T18:00:00Z",
          "detour": "300s"
        },
        {
          "shipmentIndex": 1,
          "startTime": "2023-01-13T18:07:42Z",
          "detour": "493s"
        },
        {
          "shipmentIndex": 2,
          "startTime": "2023-01-13T18:17:27Z",
          "detour": "873s"
        }
      ],
      "transitions": [
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:48:35Z"
        },
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:51:05Z"
        },
        {
          "travelDuration": "0s",
          "waitDuration": "0s",
          "totalDuration": "0s",
          "startTime": "2023-01-13T17:53:35Z"
        },
        {
          "travelDuration": "235s",
          "travelDistanceMeters": 795,
          "waitDuration": "0s",
          "totalDuration": "235s",
          "startTime": "2023-01-13T17:56:05Z"
        },
        {
          "travelDuration": "212s",
          "travelDistanceMeters": 791,
          "waitDuration": "0s",
          "totalDuration": "212s",
          "startTime": "2023-01-13T18:04:10Z"
        },
        {
          "travelDuration": "335s",
          "travelDistanceMeters": 1204,
          "waitDuration": "0s",
          "totalDuration": "335s",
          "startTime": "2023-01-13T18:11:52Z"
        },
        {
          "travelDuration": "171s",
          "travelDistanceMeters": 665,
          "waitDuration": "0s",
          "totalDuration": "171s",
          "startTime": "2023-01-13T18:21:37Z"
        }
      ],
      "metrics": {
        "performedShipmentCount": 3,
        "travelDuration": "953s",
        "waitDuration": "0s",
        "delayDuration": "0s",
        "breakDuration": "0s",
        "visitDuration": "1200s",
        "totalDuration": "2153s",
        "travelDistanceMeters": 3455
      },
      "routeCosts": {
        "model.shipments.deliveries.time_windows.cost_per_hour_after_soft_end_time": 0.58166666666666667,
        "model.shipments.deliveries.time_windows.cost_per_hour_before_soft_start_time": 5.7433333333333332,
        "model.vehicles.cost_per_hour": 23.922222222222221,
        "model.vehicles.cost_per_kilometer": 34.55
      },
      "routeTotalCost": 64.797222222222217
    }
  ],
  "metrics": {
    "aggregatedRouteMetrics": {
      "performedShipmentCount": 3,
      "travelDuration": "953s",
      "waitDuration": "0s",
      "delayDuration": "0s",
      "breakDuration": "0s",
      "visitDuration": "1200s",
      "totalDuration": "2153s",
      "travelDistanceMeters": 3455
    },
    "usedVehicleCount": 1,
    "earliestVehicleStartTime": "2023-01-13T17:48:35Z",
    "latestVehicleEndTime": "2023-01-13T18:24:28Z",
    "totalCost": 64.797222222222217,
    "costs": {
      "model.vehicles.cost_per_kilometer": 34.55,
      "model.shipments.deliveries.time_windows.cost_per_hour_before_soft_start_time": 5.7433333333333332,
      "model.shipments.deliveries.time_windows.cost_per_hour_after_soft_end_time": 0.58166666666666667,
      "model.vehicles.cost_per_hour": 23.922222222222221
    }
  }
}
    

在只有硬性時間區間限制的範例中,shipment[1] 會完全略過,而如果將其提交時間區間調低,就會在時間區間開始時間之前提交。同樣地,將其他出貨作業的結束時間調低,可讓 shipment[2]時間窗口結束後送達。

同時,費用和總出貨量也有所變動:

  • totalCost:從 81.283 減少至 64.797
  • 已完成的出貨量:從 2 增加至 3

與前一個範例相比,時間視窗限制較為寬鬆,因此最佳化工具找到了成本較低的解決方案。

最後,metrics.costs 屬性也包含一個新鍵,用於根據限制條件和未達的提交時間長度,指出實際產生的成本。也就是:

  • costPerHourBeforeSoftStartTime 2.0 和
  • 實際送達時間與時間範圍開始時間之間的時間差距: 2.83583 小時

結果:

model.shipments.deliveries.time_windows.cost_per_hour_before_soft_start_time:5.6716666666666669。

您可以使用這些指標進行成本分析,瞭解硬式限制和軟式限制之間的權衡,並據此調整限制,以便更符合特定業務規則。在這種情況下,總費用低於 shipment[1].penalty_cost 的 20.0。最佳化工具判斷,提早出貨比略過出貨更具成本效益