最大運転時間を制限する
maxDrivingTimeは、サービス時間、待機時間、休憩時間などの他の活動とは独立して、シフト中に車両が実際に走行できる累積時間の上限を設定します。このプロパティを使用することで、シフトの長さに関係なく、1回のシフトあたりの運転時間を一定時間内に収めることを義務付ける欧州連合 (EU) の運転時間規則などの法規制に準拠した運行管理を実現できます。
最大シフト時間を制限することは、広範な地理的エリアで車両を運行する運行管理にとっても有益です。このような場合、シフト時間は短くても、累積運転時間が長くなることがあります。そのため、maxDrivingTime制約を設定することで、最適化アルゴリズムが1回のシフトで1台の車両に、地理的に離れた多数のジョブを割り当てるのを防ぐことができます。
注
法規制への適合を正確にモデル化するには、
shiftTimeとmaxDrivingTimeの違いを理解することが重要です。shiftTimeパラメーターは、車両タイプの合計作業時間 (運転+サービス+待機+休憩) を制限するのに対し、maxDrivingTimeは運転時間のみを対象とします。たとえば、
shiftTimeが12時間、maxDrivingTimeが5時間に設定された車両では、残りのシフト時間をサービスや待機に充てることはできますが、シフト時間に余裕があっても5時間を超えて運転することはできません。合計シフト時間とは別に、車両タイプの最大シフト時間を制限する方法については、「最大シフト時間を制限する」を参照してください。
limits.maxDrivingTimeは、車両タイプの設定の一部として秒単位の整数値で指定します。次の例を参照してください。
{
"fleet": {
"types": [
{
"profile": "car",
"amount": 2,
"capacity": [
50
],
"costs": {
"time": 0.002,
"distance": 0.001,
"fixed": 10
},
"id": "vehicle_1",
"shifts": [
{
"start": {
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": "2024-06-24T08:00:00+02:00"
},
"end": {
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": "2024-06-24T20:00:00+02:00"
}
}
],
"limits": {
// Maximum driving time for the vehicle type (5 hrs)
"maxDrivingTime": 18000
}
}
],
"profiles": [
{
"name": "car",
"type": "car"
}
]
}
// Remaining problem components...
}複数車両からなる運行管理全体で運転時間を制限する
maxDrivingTime機能を具体的な例で説明するために、ベルリンにある倉庫を想定してみましょう。この拠点には乗用車プロファイルの車両が2台あり、それぞれの積載容量は50、シフトの稼働時間は08:00から20:00で、1回のシフトあたりの運転時間の上限は18,000秒 (5時間) に制限されています。このサンプルユースケースの運行管理では、ベルリン都市圏に分散する49のジョブを処理する必要があります。
maxDrivingTime制約を指定することで、1台の車両がすべてのジョブを処理するために必要な累積運転時間を超える場合、最適化アルゴリズムがそのジョブを2台の利用可能な車両に分割します。
車両の運転時間制限を超える原因となるジョブは、すべて2台目の車両に再割り当てされます。両方の車両がすべてのジョブを完了する前にそれぞれの制限に達した場合、残りのジョブはソリューション内のunassignedリストに表示されます。
問題設定の詳細については、次のセクションを参照してください。
注
サービス時間 (ジョブあたり
duration: 300) はmaxDrivingTimeに含まれません。カウントされるのは、道路上の走行時間のみです。
Click to expand/collapse the sample JSON
{
"fleet": {
"types": [
{
"profile": "car",
"amount": 2,
"capacity": [
50
],
"costs": {
"time": 0.002,
"distance": 0.001,
"fixed": 10
},
"id": "vehicle_1",
"shifts": [
{
"start": {
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": "2024-06-24T08:00:00+02:00"
},
"end": {
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": "2024-06-24T20:00:00+02:00"
}
}
],
"limits": {
"maxDrivingTime": 18000
}
}
],
"profiles": [
{
"name": "car",
"type": "car"
}
]
},
"plan": {
"jobs": [
{
"id": "Job_1",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.63329,
"lng": 13.3138
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_2",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.62738533184079,
"lng": 13.3789
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_3",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.51635175288175,
"lng": 13.343661020679571
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_4",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.456,
"lng": 13.403260583257188
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_5",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.63256,
"lng": 13.37322
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_6",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.45810373923444,
"lng": 13.331808942475499
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_7",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.439442845393685,
"lng": 13.336118100685782
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_8",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.53213114000045,
"lng": 13.373517153879769
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_9",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.4823,
"lng": 13.4703
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_10",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.5313,
"lng": 13.35356
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_11",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.457844833248835,
"lng": 13.322525701671735
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_12",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.4329271708958,
"lng": 13.376558539227483
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_13",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.48128598928299,
"lng": 13.4944
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_14",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.580380893737356,
"lng": 13.304479222218161
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_15",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.444597854004236,
"lng": 13.42729037972278
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_16",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.5102,
"lng": 13.3444
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_17",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.48903177127663,
"lng": 13.495944342993262
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_18",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.62863,
"lng": 13.3621182
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_19",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.65831976801964,
"lng": 13.359646771531477
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_20",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.61955,
"lng": 13.29845
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_21",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.49949154428338,
"lng": 13.40857671284082
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_22",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.465255531970406,
"lng": 13.511537556934355
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_23",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.4312,
"lng": 13.45023
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_24",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.5293,
"lng": 13.38507204916371
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_25",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.6378,
"lng": 13.48675
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_26",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.53754,
"lng": 13.34152
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_27",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.48811100200862,
"lng": 13.376
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_28",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.4745,
"lng": 13.42
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_29",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.58884270031872,
"lng": 13.352068415230912
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_30",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.60079217247425,
"lng": 13.339813254226156
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_31",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.4779,
"lng": 13.5012
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_32",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.60066027234286,
"lng": 13.502741838681837
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_33",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.55437436208552,
"lng": 13.503142187091647
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_34",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.48446152479127,
"lng": 13.392004256315916
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_35",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.482203294624796,
"lng": 13.391214601891551
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_36",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.60842932011795,
"lng": 13.46922174529483
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_37",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.47651505101506,
"lng": 13.459944175857151
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_38",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.50488105730338,
"lng": 13.355333507786808
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_39",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.6029,
"lng": 13.3113
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_40",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.6543,
"lng": 13.39278
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_41",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.51508491755749,
"lng": 13.38
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_42",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.63313572894435,
"lng": 13.506488581249922
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_43",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.459450803409204,
"lng": 13.396015195980405
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_44",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.54433793446157,
"lng": 13.49579242116612
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_45",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.486517527979494,
"lng": 13.382057792236846
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_46",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.55606147412602,
"lng": 13.41517487839967
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_47",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.591995183321515,
"lng": 13.36000789424169
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_48",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.56223251898173,
"lng": 13.471999398223556
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_49",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.595251760429065,
"lng": 13.456764166098564
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
}
]
}
}ソリューション
次の図は、サンプルユースケースで示した問題のソリューションを視覚化したものです。
視覚化が示すように、最適化アルゴリズムは、割り当てられたジョブを完了するために2台の車両を選択しました。以下の表は、各車両の主要な統計をまとめたものです。5時間 (18,000秒) の制限に対する運転時間が強調表示されています。
| メトリック | vehicle_1_1 | vehicle_1_2 |
|---|---|---|
| 割り当てられたジョブ | 18 | 31 |
| 運転時間 | 2時間19分 (8,350秒) | 4時間5分 (14,690秒) |
| サービス時間 | 1時間30分 (5,400秒) | 2時間35分 (9,300秒) |
| 旅程の所要時間 | 3時間49分 (13,750秒) | 6時間40分 (23,990秒) |
| 走行距離 | 69.2 km | 119.1 km |
| コスト | 106.72 | 177.04 |
サンプル問題で指定された車両タイプはcapacityが50に設定されており、本来であれば1台の車両だけで指定のシフト内にすべてのジョブを完了させることが可能でした。しかし、maxDrivingTimeの制約があったため、アルゴリズムは旅程を2台の車両に分割せざるを得ませんでした。この分割のおかげで、どちらの車両も最大運転時間の制限を超えることはありませんでした。
次のセクションに完全なソリューションのJSONを示します。
Click to expand/collapse the sample JSON
{
"statistic": {
"cost": 283.762,
"distance": 188282,
"duration": 37740,
"times": {
"driving": 23040,
"serving": 14700,
"waiting": 0,
"stopping": 0,
"break": 0,
"intraStop": 0
},
"intraStopDistance": 0
},
"tours": [
{
"vehicleId": "vehicle_1_2",
"typeId": "vehicle_1",
"stops": [
{
"time": {
"arrival": "2024-06-24T06:00:00Z",
"departure": "2024-06-24T06:00:00Z"
},
"load": [
31
],
"activities": [
{
"jobId": "departure",
"type": "departure",
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": {
"start": "2024-06-24T06:00:00Z",
"end": "2024-06-24T06:00:00Z",
"arrival": "2024-06-24T06:00:00Z"
}
}
],
"location": {
"lat": 52.531,
"lng": 13.38461
},
"distance": 0
},
{
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}次のステップ
- 純粋な運転時間ではなく合計勤務時間を制限する方法については、「最大シフト時間を制限する」を参照してください。
- 車両の走行距離の上限を設定する方法については、「最大距離を制限する」を参照してください。
- 1回のシフトあたりの車両の停車回数を制御する方法については、「停車地の最大数を設定する」を参照してください。
- HERE Tour Planning APIのメソッド、エンドポイント、パラメーターの詳細については、「APIリファレンス」を参照してください。
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