Optimize car routes by travel time or distance
The car profile allows you to adjust the route calculation mode depending on your business requirements which affects how the optimization algorithm calculates routes between all stops in the tour. The following modes are available:
fast(default): Minimizes time on roadshort: Minimizes mileage
Fast mode - optimize by travel time
The fast mode optimizes routes by minimizing the total travel time. This mode considers such speed information as typical travel speeds of different road types (for example, highways, arterial roads, residential streets, and so on), traffic conditions, and speed limits to calculate realistic travel times. This default mode covers most business use cases such as time-sensitive deliveries (for example, same-day delivery or express courier services).
Short mode - optimize by distance
This mode optimizes routes by minimizing the total distance that a vehicle covers during a tour. In this mode, the optimization algorithm explicitly disregards any speed information entirely and looks only at the physical distance between points, attempting to minimize that distance, without considering how fast a vehicle can drive on different roads. This mode is particularly well-suited for cost-sensitive operation in which factors such as reducing fuel consumption are crucial (for example, to meet environmental compliance goals or for mileage-based cost reduction use cases).
Note
The
shortmode does NOT necessarily produce the absolute shortest distance, as the optimization algorithm keeps the routes as sensible as possible, for example, by penalizing unnecessary turns.
Understand car profile mode configuration
In the problem specification, you configure the mode property within the fleet.profiles object for the car profile, as shown in the following snippet:
{
"fleet": {
"profiles": [
{
"name": "quick_delivery_vehicle",
"type": "car",
"mode": "short"
}
]
}
}The mode you selected for a car profile applies to all routing calculations for that profile throughout the tour. If you do not specify the mode property, the optimization algorithm uses the fast mode by default.
Understand how mode interacts with other optimization settings
The mode property controls the routing matrix calculations (returning either faster travel times or shorter distances between location, depending on the mode selected), but the final optimization depends on the following configuration:
By understanding this relationship, you can avoid getting mixed or unexpected results.
Align mode with vehicle costs
The optimization algorithm uses vehicle costs as one of the main factors for evaluating routing decisions. By default, if you don't specify objectives, the system use the following objective function configuration: [{type: "minimizeUnassigned"}, {type: "minimizeTours"}, {type: "minimizeCost"}]. The minimizeCost objective is sensitive to your costs.distance and costs.time configuration:
{
"costs": {
"distance": 0.001, // Cost per meter
"time": 0.002, // Cost per second
"fixed": 10
}
}Setting mode to short requests distance-optimized routes. However, if costs.time significantly outweighs cost.distance or cost.distance equals 0, the optimization algorithm might still prioritize time-based decisions when building the tour.
Note
Specifying
excessCoststhat penalize violating maximum distance limits might also cause the optimization algorithm to favor time-based solutions, even if you setmodetoshort.
To ensure results consistent with the selected mode, adjust the costs weights properly. For example, if using the short option, put a higher weight on costs.distance and lower weight on costs.time, for example:
{
"fleet": {
"types": [{
"costs": {
"distance": 0.002, // Higher weight on distance
"time": 0.0001, // Lower weight on time
"fixed": 10
}
}],
"profiles": [{
"type": "car",
"mode": "short" // Request distance-optimized routes
}]
}
}Note
Adjust
costsweights based on your individual business requirements.
Align with objectives
If you specify objectives explicitly, make sure that the objectives that you set align with your mode setting. For example, if you specify mode as fast but then include the minimizeDistance objective, the mode setting might take little effect, because mode: "fast" provides time-optimized routes, but minimizeDistance tells the optimization algorithm to minimize distance, which creates a mismatch.
The same is true if you set mode to short while including the minimizeDuration objective in your problem. An example of aligned configuration includes:
{
"profiles": [{"type": "car", "mode": "short"}],
"objectives": [
{"type": "minimizeUnassigned"},
{"type": "minimizeDistance"} // Aligns with short mode
]
}For more information, see Using objective functions.
Compare route optimization modes
The following sections provide a practical demonstration of the difference between fast and short profiles. The comparison scenario involves two problems including the same set of jobs, same vehicles, and the same start and end locations in Berlin.
The purpose of the comparison is to showcase the trade-off between minimizing travel time versus minimizing distance. With the fast mode, the optimization algorithm might choose longer distances if they result in faster times (for example, by selecting highways or high-speed roads). Conversely, in the short mode, the optimization algorithm prioritizes shorter distances, even at the cost of increased travel time.
Problem with fast mode (default)
This problem uses the default fast mode for route calculation and has the following configuration:
- 49 delivery jobs scattered across Berlin served by a single vehicle
- Vehicle profile set to
carwith the default mode - 12-hour shift time (from
8:00to20:00) - Vehicle capacity set to 50 units
- The vehicle starts and ends at the same Berlin location (lat:
52.531, lng:13.38461) - The time-based cost (
0.002per second) and distance-based cost (0.001per meter)
See the following snippet for the full problem definition:
Click to expand/collapse the sample JSON
{
"fleet": {
"types": [
{
"profile": "car",
"amount": 1,
"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"
}
}
]
}
],
"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
]
}
]
}
}
]
}
}Solution with fast mode
The fast mode solution produced the following key statistics:
- Total cost: 267.88
- Total distance: 182,668 meters (≈182.7 km)
- Total duration: 37,605 seconds (≈10.4 hours)
- Driving time: 22,905 seconds (≈6.4 hours)
- Service time: 14,700 seconds (≈4.1 hours)
All 49 jobs were successfully assigned and completed. The route sequence was optimized to minimize the time spent traveling.
See the following snippet for the full problem solution:
Click to expand/collapse the sample JSON
{
"statistic": {
"cost": 267.87800000000004,
"distance": 182668,
"duration": 37605,
"times": {
"driving": 22905,
"serving": 14700,
"waiting": 0,
"stopping": 0,
"break": 0,
"intraStop": 0
},
"intraStopDistance": 0
},
"tours": [
{
"vehicleId": "vehicle_1_1",
"typeId": "vehicle_1",
"stops": [
{
"time": {
"arrival": "2024-06-24T06:00:00Z",
"departure": "2024-06-24T06:00:00Z"
},
"load": [
49
],
"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
},
{
"time": {
"arrival": "2024-06-24T06:02:22Z",
"departure": "2024-06-24T06:07:22Z"
},
"load": [
48
],
"activities": [
{
"jobId": "Job_8",
"type": "delivery",
"location": {
"lat": 52.53213114000045,
"lng": 13.373517153879767
},
"time": {
"start": "2024-06-24T06:02:22Z",
"end": "2024-06-24T06:07:22Z",
"arrival": "2024-06-24T06:02:22Z"
}
}
],
"location": {
"lat": 52.53213114000045,
"lng": 13.373517153879767
},
"distance": 1079
},
{
"time": {
"arrival": "2024-06-24T06:10:45Z",
"departure": "2024-06-24T06:15:45Z"
},
"load": [
47
],
"activities": [
{
"jobId": "Job_24",
"type": "delivery",
"location": {
"lat": 52.5293,
"lng": 13.38507204916371
},
"time": {
"start": "2024-06-24T06:10:45Z",
"end": "2024-06-24T06:15:45Z",
"arrival": "2024-06-24T06:10:45Z"
}
}
],
"location": {
"lat": 52.5293,
"lng": 13.38507204916371
},
"distance": 2276
},
{
"time": {
"arrival": "2024-06-24T06:21:35Z",
"departure": "2024-06-24T06:26:35Z"
},
"load": [
46
],
"activities": [
{
"jobId": "Job_41",
"type": "delivery",
"location": {
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"time": {
"arrival": "2024-06-24T13:24:26Z",
"departure": "2024-06-24T13:29:26Z"
},
"load": [
13
],
"activities": [
{
"jobId": "Job_19",
"type": "delivery",
"location": {
"lat": 52.65831976801964,
"lng": 13.359646771531477
},
"time": {
"start": "2024-06-24T13:24:26Z",
"end": "2024-06-24T13:29:26Z",
"arrival": "2024-06-24T13:24:26Z"
}
}
],
"location": {
"lat": 52.65831976801964,
"lng": 13.359646771531477
},
"distance": 119970
},
{
"time": {
"arrival": "2024-06-24T13:34:34Z",
"departure": "2024-06-24T13:39:34Z"
},
"load": [
12
],
"activities": [
{
"jobId": "Job_40",
"type": "delivery",
"location": {
"lat": 52.6543,
"lng": 13.39278
},
"time": {
"start": "2024-06-24T13:34:34Z",
"end": "2024-06-24T13:39:34Z",
"arrival": "2024-06-24T13:34:34Z"
}
}
],
"location": {
"lat": 52.6543,
"lng": 13.39278
},
"distance": 122690
},
{
"time": {
"arrival": "2024-06-24T13:50:21Z",
"departure": "2024-06-24T13:55:21Z"
},
"load": [
11
],
"activities": [
{
"jobId": "Job_18",
"type": "delivery",
"location": {
"lat": 52.62863,
"lng": 13.3621182
},
"time": {
"start": "2024-06-24T13:50:21Z",
"end": "2024-06-24T13:55:21Z",
"arrival": "2024-06-24T13:50:21Z"
}
}
],
"location": {
"lat": 52.62863,
"lng": 13.3621182
},
"distance": 128415
},
{
"time": {
"arrival": "2024-06-24T13:58:15Z",
"departure": "2024-06-24T14:03:15Z"
},
"load": [
10
],
"activities": [
{
"jobId": "Job_5",
"type": "delivery",
"location": {
"lat": 52.63256,
"lng": 13.37322
},
"time": {
"start": "2024-06-24T13:58:15Z",
"end": "2024-06-24T14:03:15Z",
"arrival": "2024-06-24T13:58:15Z"
}
}
],
"location": {
"lat": 52.63256,
"lng": 13.37322
},
"distance": 129467
},
{
"time": {
"arrival": "2024-06-24T14:08:30Z",
"departure": "2024-06-24T14:13:30Z"
},
"load": [
9
],
"activities": [
{
"jobId": "Job_2",
"type": "delivery",
"location": {
"lat": 52.62738533184079,
"lng": 13.3789
},
"time": {
"start": "2024-06-24T14:08:30Z",
"end": "2024-06-24T14:13:30Z",
"arrival": "2024-06-24T14:08:30Z"
}
}
],
"location": {
"lat": 52.62738533184079,
"lng": 13.3789
},
"distance": 131659
},
{
"time": {
"arrival": "2024-06-24T14:29:14Z",
"departure": "2024-06-24T14:34:14Z"
},
"load": [
8
],
"activities": [
{
"jobId": "Job_49",
"type": "delivery",
"location": {
"lat": 52.595251760429065,
"lng": 13.456764166098564
},
"time": {
"start": "2024-06-24T14:29:14Z",
"end": "2024-06-24T14:34:14Z",
"arrival": "2024-06-24T14:29:14Z"
}
}
],
"location": {
"lat": 52.595251760429065,
"lng": 13.456764166098564
},
"distance": 140902
},
{
"time": {
"arrival": "2024-06-24T14:39:51Z",
"departure": "2024-06-24T14:44:51Z"
},
"load": [
7
],
"activities": [
{
"jobId": "Job_36",
"type": "delivery",
"location": {
"lat": 52.60842932011795,
"lng": 13.46922174529483
},
"time": {
"start": "2024-06-24T14:39:51Z",
"end": "2024-06-24T14:44:51Z",
"arrival": "2024-06-24T14:39:51Z"
}
}
],
"location": {
"lat": 52.60842932011795,
"lng": 13.46922174529483
},
"distance": 143746
},
{
"time": {
"arrival": "2024-06-24T14:54:23Z",
"departure": "2024-06-24T14:59:23Z"
},
"load": [
6
],
"activities": [
{
"jobId": "Job_25",
"type": "delivery",
"location": {
"lat": 52.6378,
"lng": 13.48675
},
"time": {
"start": "2024-06-24T14:54:23Z",
"end": "2024-06-24T14:59:23Z",
"arrival": "2024-06-24T14:54:23Z"
}
}
],
"location": {
"lat": 52.6378,
"lng": 13.48675
},
"distance": 148984
},
{
"time": {
"arrival": "2024-06-24T15:03:48Z",
"departure": "2024-06-24T15:08:48Z"
},
"load": [
5
],
"activities": [
{
"jobId": "Job_42",
"type": "delivery",
"location": {
"lat": 52.63313572894435,
"lng": 13.506488581249922
},
"time": {
"start": "2024-06-24T15:03:48Z",
"end": "2024-06-24T15:08:48Z",
"arrival": "2024-06-24T15:03:48Z"
}
}
],
"location": {
"lat": 52.63313572894435,
"lng": 13.506488581249922
},
"distance": 150543
},
{
"time": {
"arrival": "2024-06-24T15:20:46Z",
"departure": "2024-06-24T15:25:46Z"
},
"load": [
4
],
"activities": [
{
"jobId": "Job_32",
"type": "delivery",
"location": {
"lat": 52.60066027234286,
"lng": 13.502741838681835
},
"time": {
"start": "2024-06-24T15:20:46Z",
"end": "2024-06-24T15:25:46Z",
"arrival": "2024-06-24T15:20:46Z"
}
}
],
"location": {
"lat": 52.60066027234286,
"lng": 13.502741838681835
},
"distance": 159363
},
{
"time": {
"arrival": "2024-06-24T15:33:50Z",
"departure": "2024-06-24T15:38:50Z"
},
"load": [
3
],
"activities": [
{
"jobId": "Job_48",
"type": "delivery",
"location": {
"lat": 52.56223251898173,
"lng": 13.471999398223556
},
"time": {
"start": "2024-06-24T15:33:50Z",
"end": "2024-06-24T15:38:50Z",
"arrival": "2024-06-24T15:33:50Z"
}
}
],
"location": {
"lat": 52.56223251898173,
"lng": 13.471999398223556
},
"distance": 165024
},
{
"time": {
"arrival": "2024-06-24T15:44:48Z",
"departure": "2024-06-24T15:49:48Z"
},
"load": [
2
],
"activities": [
{
"jobId": "Job_33",
"type": "delivery",
"location": {
"lat": 52.55437436208552,
"lng": 13.503142187091647
},
"time": {
"start": "2024-06-24T15:44:48Z",
"end": "2024-06-24T15:49:48Z",
"arrival": "2024-06-24T15:44:48Z"
}
}
],
"location": {
"lat": 52.55437436208552,
"lng": 13.503142187091647
},
"distance": 168895
},
{
"time": {
"arrival": "2024-06-24T15:53:38Z",
"departure": "2024-06-24T15:58:38Z"
},
"load": [
1
],
"activities": [
{
"jobId": "Job_44",
"type": "delivery",
"location": {
"lat": 52.54433793446157,
"lng": 13.49579242116612
},
"time": {
"start": "2024-06-24T15:53:38Z",
"end": "2024-06-24T15:58:38Z",
"arrival": "2024-06-24T15:53:38Z"
}
}
],
"location": {
"lat": 52.54433793446157,
"lng": 13.49579242116612
},
"distance": 170540
},
{
"time": {
"arrival": "2024-06-24T16:13:07Z",
"departure": "2024-06-24T16:18:07Z"
},
"load": [
0
],
"activities": [
{
"jobId": "Job_46",
"type": "delivery",
"location": {
"lat": 52.55606147412602,
"lng": 13.41517487839967
},
"time": {
"start": "2024-06-24T16:13:07Z",
"end": "2024-06-24T16:18:07Z",
"arrival": "2024-06-24T16:13:07Z"
}
}
],
"location": {
"lat": 52.55606147412602,
"lng": 13.41517487839967
},
"distance": 178123
},
{
"time": {
"arrival": "2024-06-24T16:26:45Z",
"departure": "2024-06-24T16:26:45Z"
},
"load": [
0
],
"activities": [
{
"jobId": "arrival",
"type": "arrival",
"location": {
"lat": 52.531,
"lng": 13.38461
},
"time": {
"start": "2024-06-24T16:26:45Z",
"end": "2024-06-24T16:26:45Z",
"arrival": "2024-06-24T16:26:45Z"
}
}
],
"location": {
"lat": 52.531,
"lng": 13.38461
},
"distance": 182668
}
],
"statistic": {
"cost": 267.87800000000004,
"distance": 182668,
"duration": 37605,
"times": {
"driving": 22905,
"serving": 14700,
"waiting": 0,
"stopping": 0,
"break": 0,
"intraStop": 0
},
"intraStopDistance": 0
},
"shiftIndex": 0
}
]
}Problem with short mode
The following problem is identical to the fast mode example, except for the mode property, now set to short. This instructs the optimization algorithm to minimize total distance traveled (while still considering turns and sensible routing), which might result in longer travel times, but lower mileage.
See the following snippet for the full problem definition:
Click to expand/collapse the sample JSON
{
"fleet": {
"types": [
{
"profile": "car",
"amount": 1,
"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"
}
}
]
}
],
"profiles": [
{
"name": "car",
"type": "car",
"mode": "short"
}
]
},
"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": [
{
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"lat": 52.6029,
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},
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}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_40",
"tasks": {
"deliveries": [
{
"places": [
{
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"lat": 52.6543,
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},
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}
],
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1
]
}
]
}
},
{
"id": "Job_41",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.51508491755749,
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},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_42",
"tasks": {
"deliveries": [
{
"places": [
{
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"lat": 52.63313572894435,
"lng": 13.506488581249922
},
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}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_43",
"tasks": {
"deliveries": [
{
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{
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"lat": 52.459450803409204,
"lng": 13.396015195980405
},
"duration": 300
}
],
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1
]
}
]
}
},
{
"id": "Job_44",
"tasks": {
"deliveries": [
{
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{
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"lat": 52.54433793446157,
"lng": 13.49579242116612
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_45",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.486517527979494,
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},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_46",
"tasks": {
"deliveries": [
{
"places": [
{
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"lat": 52.55606147412602,
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},
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}
],
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1
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}
]
}
},
{
"id": "Job_47",
"tasks": {
"deliveries": [
{
"places": [
{
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"lat": 52.591995183321515,
"lng": 13.36000789424169
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_48",
"tasks": {
"deliveries": [
{
"places": [
{
"location": {
"lat": 52.56223251898173,
"lng": 13.471999398223556
},
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}
],
"demand": [
1
]
}
]
}
},
{
"id": "Job_49",
"tasks": {
"deliveries": [
{
"places": [
{
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"lat": 52.595251760429065,
"lng": 13.456764166098564
},
"duration": 300
}
],
"demand": [
1
]
}
]
}
}
]
}
}Solution with short mode
The short mode solution produced the following key statistics:
- Total cost: 260.52
- Total distance: 175,511 meters (≈175.5 km)
- Total duration: 37,503 seconds (≈10.4 hours)
- Driving time: 22,803 seconds (≈6.3 hours)
- Service time: 14,700 seconds (≈4.1 hours)
See the following snippet for the full problem solution:
Click to expand/collapse the sample JSON
{
"statistic": {
"cost": 260.517,
"distance": 175511,
"duration": 37503,
"times": {
"driving": 22803,
"serving": 14700,
"waiting": 0,
"stopping": 0,
"break": 0,
"intraStop": 0
},
"intraStopDistance": 0
},
"tours": [
{
"vehicleId": "vehicle_1_1",
"typeId": "vehicle_1",
"stops": [
{
"time": {
"arrival": "2024-06-24T06:00:00Z",
"departure": "2024-06-24T06:00:00Z"
},
"load": [
49
],
"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
},
{
"time": {
"arrival": "2024-06-24T06:01:15Z",
"departure": "2024-06-24T06:06:15Z"
},
"load": [
48
],
"activities": [
{
"jobId": "Job_24",
"type": "delivery",
"location": {
"lat": 52.5293,
"lng": 13.38507204916371
},
"time": {
"start": "2024-06-24T06:01:15Z",
"end": "2024-06-24T06:06:15Z",
"arrival": "2024-06-24T06:01:15Z"
}
}
],
"location": {
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},
"distance": 485
},
{
"time": {
"arrival": "2024-06-24T06:09:43Z",
"departure": "2024-06-24T06:14:43Z"
},
"load": [
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],
"activities": [
{
"jobId": "Job_8",
"type": "delivery",
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"lng": 13.373517153879767
},
"time": {
"start": "2024-06-24T06:09:43Z",
"end": "2024-06-24T06:14:43Z",
"arrival": "2024-06-24T06:09:43Z"
}
}
],
"location": {
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"lng": 13.373517153879767
},
"distance": 1679
},
{
"time": {
"arrival": "2024-06-24T06:20:38Z",
"departure": "2024-06-24T06:25:38Z"
},
"load": [
46
],
"activities": [
{
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"type": "delivery",
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},
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"end": "2024-06-24T06:25:38Z",
"arrival": "2024-06-24T06:20:38Z"
}
}
],
"location": {
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},
"distance": 4551
},
{
"time": {
"arrival": "2024-06-24T06:30:00Z",
"departure": "2024-06-24T06:35:00Z"
},
"load": [
45
],
"activities": [
{
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"type": "delivery",
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},
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"end": "2024-06-24T06:35:00Z",
"arrival": "2024-06-24T06:30:00Z"
}
}
],
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},
"distance": 6353
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{
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"departure": "2024-06-24T06:46:45Z"
},
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],
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{
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}
}
],
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{
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"departure": "2024-06-24T06:56:54Z"
},
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43
],
"activities": [
{
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},
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"end": "2024-06-24T06:56:54Z",
"arrival": "2024-06-24T06:51:54Z"
}
}
],
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},
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},
{
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"departure": "2024-06-24T07:06:03Z"
},
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42
],
"activities": [
{
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},
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"arrival": "2024-06-24T07:01:03Z"
}
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],
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{
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},
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41
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{
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},
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}
}
],
"location": {
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},
"distance": 16161
},
{
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"departure": "2024-06-24T07:29:31Z"
},
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40
],
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{
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},
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"end": "2024-06-24T07:29:31Z",
"arrival": "2024-06-24T07:24:31Z"
}
}
],
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},
"distance": 19563
},
{
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"departure": "2024-06-24T07:42:08Z"
},
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39
],
"activities": [
{
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"lng": 13.376
},
"time": {
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"end": "2024-06-24T07:42:08Z",
"arrival": "2024-06-24T07:37:08Z"
}
}
],
"location": {
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},
"distance": 22884
},
{
"time": {
"arrival": "2024-06-24T07:46:09Z",
"departure": "2024-06-24T07:51:09Z"
},
"load": [
38
],
"activities": [
{
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},
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"end": "2024-06-24T07:51:09Z",
"arrival": "2024-06-24T07:46:09Z"
}
}
],
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},
"distance": 24096
},
{
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},
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37
],
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{
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],
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{
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},
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36
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{
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},
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"arrival": "2024-06-24T08:07:45Z"
}
}
],
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},
"distance": 26874
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{
"time": {
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},
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{
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},
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"arrival": "2024-06-24T08:23:03Z"
}
}
],
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},
"distance": 30081
},
{
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},
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{
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}
}
],
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{
"time": {
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},
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{
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},
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"arrival": "2024-06-24T08:50:35Z"
}
}
],
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},
"distance": 38880
},
{
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},
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}
],
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"distance": 46485
},
{
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},
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31
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{
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}
],
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{
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},
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30
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{
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}
}
],
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{
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},
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29
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{
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}
],
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{
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},
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28
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{
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],
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{
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},
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{
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"end": "2024-06-24T10:07:34Z",
"arrival": "2024-06-24T10:02:34Z"
}
}
],
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"distance": 60405
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{
"time": {
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"departure": "2024-06-24T10:25:37Z"
},
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26
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"activities": [
{
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}
],
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},
"distance": 66754
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{
"time": {
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"departure": "2024-06-24T10:36:48Z"
},
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25
],
"activities": [
{
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"end": "2024-06-24T10:36:48Z",
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}
}
],
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"distance": 69149
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{
"time": {
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},
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"activities": [
{
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],
"statistic": {
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"distance": 175511,
"duration": 37503,
"times": {
"driving": 22803,
"serving": 14700,
"waiting": 0,
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]
}Comparison of results
The following table compares the key metrics between fast mode and short mode optimization for the car profile:
| Metric | Fast Mode | Short Mode | Difference |
|---|---|---|---|
| Total cost | 267.88 | 260.52 | -7.36 (2.7% savings) |
| Total distance | 182,668 m (182.7 km) | 175,511 m (175.5 km) | -7,157 m (-7.2 km, 3.9% reduction) |
| Total duration | 37,605 s (10.4 hrs) | 37,503 s (10.4 hrs) | -102 s (-1.7 min, 0.3% reduction) |
Based on the key statistics for the compared tours:
- Short mode achieved 7.2 km less distance traveled, resulting in lower fuel consumption and mileage-based costs
- The total cost decreased by 2.7% due to the reduced distance component
- The
shortmode also achieved a slightly faster total duration (1.7 minutes saved), likely due to more direct routing - Both modes successfully completed all 49 jobs within the shift constraints
The following comparison highlights how the optimization algorithm optimizes routes in a tour, based on the selected mode:
| Fast mode | Short mode |
|---|---|
 |  |
Based on the routing decisions for job_39 and job_14, in the fast mode, the optimization algorithm routes the vehicle along a highway for a longer but faster route. In contrast, short mode prioritizes reduced distance, which could lead to potentially prolonged tour, depending on time of day and traffic intensity.
Choose the right mode for your use case
Even though short mode proved slightly more efficient in this comparison, fast mode is suitable for most scenarios. Use short mode when distance-based costs significantly outweigh time-based costs. Consider testing both modes to determine which provides better results for your specific business requirements.
Next steps
- To learn how traffic affects mode calculations, see Understand traffic modes
- For customizing route preferences in both modes, see Use preferred routes with avoid options
- To understand cost optimization, see Optimize tours for cost
- For advanced optimization control, see Use objective functions for specific optimization goals
- To visualize the route differences between modes, see Obtain route polylines for the tour
- For detailed
carprofile specifications, see API Reference
Updated 28 days ago