Vehicle Routing Problem (VRP)¶

The Vehicle Routing Problem (VRP) is a type of optimization problem that involves finding the most efficient routes for a fleet of vehicles to travel to a set of destinations and return to their starting point while satisfying a number of constraints, such as capacity and time windows. The VRP is commonly used in transportation, logistics, and delivery applications.

A Vehicle Routing Problem (VRP) Maps API refers to a set of functions or tools provided by VIETMAP that help developers to solve the VRP for a given set of locations and constraints. These APIs may provide algorithms or heuristics for finding optimal or near-optimal solutions to the VRP, as well as visualization tools for displaying the resulting routes on a map. Developers can use VRP Maps APIs to create applications that help optimize fleet operations and delivery management, such as route planning, fleet tracking, and more.

URL¶

https://maps.vietmap.vn/api/vrp?api-version=1.1&apikey={your-apikey}

Method¶

POST

Parameters¶

Key	Type	Required	Default	Example	Description
jobs	array	yes	none		Array of Job objects. Each job is a single place to visit (e.g. a delivery or pickup stop). At least one job is required.
vehicles	array	yes	none		Array of Vehicle objects describing the fleet available to serve the jobs. At least one vehicle is required.

Job Object (accept goods | release goods)¶

Key	Type	Required	Default	Example	Description
id	integer	yes	none	1	Unique identifier of the job. Must be unique across all jobs in the request.
location	array, double	yes	none	[106.112456,10.684922]	Coordinates of the job, in `[longitude, latitude]` order.
service	integer	no	0	1	Time spent servicing the job once the vehicle arrives, in seconds. Defaults to `0`.
delivery	array	no	none	[1,2]	Goods loaded at the vehicle's start and dropped off at this job. Array of integers describing multidimensional quantities (e.g. `[items, weight, volume]`); the number and order of dimensions must match the vehicle's `capacity`.
pickup	array	no	none	[1,2]	Goods collected at this job and carried back to the vehicle's end. Array of integers describing multidimensional quantities; same dimension order as `delivery` and the vehicle's `capacity`.
skills	array	no	none	[1]	Array of integers listing the skills this job requires. The job can only be served by a vehicle whose `skills` include all of these values.
priority	integer	no	0	1	Priority of including this job in the solution. Integer in the range `[0, 10]`; higher values make the job more likely to be served when not all jobs can be assigned.
time_windows	array	no	none	[[0,1400]]	Array of `[start, end]` windows during which the service may start. Times are in seconds — either relative to the planning horizon or absolute Unix timestamps (see Note). Omitting it means the job can be served at any time.

Vehicle Object (type of the vehicle)¶

Key	Type	Required	Default	Example	Description
id	integer	yes	none	1	Unique identifier of the vehicle. Must be unique across all vehicles in the request.
start	array, double	conditional	none	[106.112456,10.684922]	Coordinates where the vehicle begins its route, in `[longitude, latitude]` order. Optional, but at least one of `start` / `end` must be provided (see Note).
end	array, double	conditional	none	[106.112456,10.684922]	Coordinates where the vehicle ends its route, in `[longitude, latitude]` order. Optional, but at least one of `start` / `end` must be provided. Use the same value as `start` for a round trip.
capacity	array	no	none	[0,3]	Maximum load the vehicle can carry, as an array of integers describing multidimensional quantities (e.g. `[items, weight, volume]`). The dimension order must match the jobs' `delivery` / `pickup` arrays.
skills	array	no	none	[1]	Array of integers listing the skills this vehicle has. A job is eligible only if all of its required `skills` are present here.
time_windows	array	no	none	[[0,14400]]	Working hours of the vehicle as `[start, end]` (in seconds). Times follow the same convention as job `time_windows` (see Note). Omitting it means the vehicle has no time constraint.

Note¶

Key start and end are optional for a vehicle, as long as at least one of them is present.
If end is omitted, the resulting route will stop at the last visited job, whose choice is determined by the optimization process.
If start is omitted, the resulting route will start at the first visited job, whose choice is determined by the optimization process.
To request a round trip, just specify both start and end with the same coordinates.
Use amounts (capacity for vehicles, delivery and pickup for jobs) to describe a problem with capacity restrictions. Those arrays can be used to model custom restrictions for several metrics at once, e.g. number of items, weight, volume etc. A vehicle is only allowed to serve a set of jobs if the resulting load at each route step is lower than the matching value in capacity for each metric. When using multiple components for amounts, it is recommended to put the most important/limiting metrics first.
It is assumed that all delivery-related amounts for jobs are loaded at vehicle start, while all pickup-related amounts for jobs are brought back at vehicle end.
Use skills to describe a problem where not all jobs can be served by all vehicles. Job skills are mandatory, i.e. a job can only be served by a vehicle that has all its required skills. In other words: job j is eligible to vehicle v iff j.skills is included in v.skills.
In order to ease modeling problems with no skills required, it is assumed that there is no restriction at all if no skills keys are provided.
Useful in situations where not all jobs can be performed, to gain some control on which jobs are unassigned.
Setting a high priority value for some jobs will tend as much as possible to have them included in the solution over lower-priority jobs.

It is up to users to decide how to describe time windows:

Relative values, e.g. [0, 14400] for a 4 hours time window starting at the beginning of the planning horizon. In that case all times reported in output with the arrival key are relative to the start of the planning horizon;
Absolute values, "real" timestamps. In that case all times reported in output with the arrival key can be interpreted as timestamps. The absence of a time window in input means no timing constraint applies.
In particular, a vehicle with no time_window key will be able to serve any number of jobs, and a job with no time_windows key might be included at any time in any route, to the extent permitted by other constraints such as skills, capacity and other vehicles/jobs time windows.

Example¶

Body

href="#__codelineno-1-1">{ "vehicles": [ { "id": 1, "start": [ 106.5983012, 10.8879148 ], "end": [ 106.5983012, 10.8879148 ], "profile": "bike", "time_window": [ 1685953800, 1686418200 ], "skills": [ 1, 1000 ], "breaks": [ { "id": 1000, "time_windows": [ [ 1685966400, 1685970000 ] ], "service": 3600 }, { "id": 1, "time_windows": [ [ 1685986200, 1685988000 ] ], "service": 54000.0 }, { "id": 2000, "time_windows": [ [ 1686052800, 1686056400 ] ], "service": 3600 }, { "id": 2, "time_windows": [ [ 1686072600, 1686074400 ] ], "service": 54000.0 }, { "id": 6000, "time_windows": [ [ 1686398400, 1686402000 ] ], "service": 3600 } ], "speed_factor": 0.6 }, /// More objects should be add to here { "id": 7, "start": [ 106.7086064, 10.814915 ], "end": [ 106.7086064, 10.814915 ], "profile": "bike", "time_window": [ 1685953800, 1686418200 ], "skills": [ 1, 7000 ], "breaks": [ { "id": 1000, "time_windows": [ [ 1685966400, 1685970000 ] ], "service": 3600 }, { "id": 5, "time_windows": [ [ 1686331800, 1686333600 ] ], "service": 54000.0 }, { "id": 6000, "time_windows": [ [ 1686398400, 1686402000 ] ], "service": 3600 } ], "speed_factor": 0.6 } ], "jobs": [ { "id": 1001, "description": "HOME", "location": [ 106.5983012, 10.8879148 ], "service": 0, "priority": 3, "time_windows": [ [ 1685986200, 1685988000 ] ], "skills": [ 1000 ] }, { "id": 304, "description": "CO.OP FOOD NGUYỄN VĂN QUÁ", "location": [ 106.6287481, 10.8362058 ], "service": 1800, "time_windows": [ [ 1685948400, 1685980800 ], [ 1686034800, 1686067200 ], [ 1686121200, 1686153600 ], [ 1686207600, 1686240000 ], [ 1686294000, 1686326400 ], [ 1686380400, 1686412800 ] ], "skills": [ 1 ] }, /// More objects should be add to here { "id": 337, "description": "CO.OP FOOD TỈNH LỘ 15-1031", "location": [ 106.513876765966, 11.0885457429547 ], "service": 1800, "time_windows": [ [ 1685948400, 1685980800 ], [ 1686034800, 1686067200 ], [ 1686121200, 1686153600 ], [ 1686207600, 1686240000 ], [ 1686294000, 1686326400 ], [ 1686380400, 1686412800 ] ], "skills": [ 1 ] } ] }

Request body description¶

Vehicles¶

Parameter	Type	Description
id	number	Unique identifier of the vehicle.
start	array	Coordinates where the vehicle begins its route, in `[longitude, latitude]` order.
end	array	Coordinates where the vehicle ends its route, in `[longitude, latitude]` order. Use the same value as `start` for a round trip.
profile	string	Routing profile that determines speed and allowed roads (e.g. `bike`, `car`, `truck`).
time_window	array	Working hours of the vehicle as `[start, end]` (in seconds, Unix timestamps in this example). The vehicle only operates within this window.
skills	array	Array of integers listing the skills the vehicle has. A job is eligible only if all of its required skills are present here.
breaks	array	List of mandatory breaks the vehicle must take. Each break is an object with `id`, `time_windows` (allowed `[start, end]` slots, in seconds) and `service` (break duration, in seconds).
speed_factor	number	Multiplier applied to the profile's default speed. `< 1` slows the vehicle down, `> 1` speeds it up (e.g. `0.6` = 60% of the default speed).

Jobs¶

Parameter	Type	Description
id	number	Unique identifier of the job.
description	string	Free-text label for the job, returned as-is to help identify the stop.
location	array	Coordinates of the job, in `[longitude, latitude]` order.
service	number	Time spent servicing the job once the vehicle arrives, in seconds.
priority	number	Priority of including the job in the solution, in the range `[0, 10]`. Higher values make the job more likely to be served.
time_windows	array	Array of `[start, end]` windows (in seconds) during which the service may start. The job can have several disjoint windows.
skills	array	Array of integers listing the skills the job requires. The job can only be served by a vehicle that has all of these skills.

Response

{
    "code": 0,
    "summary": {
        "cost": 12400,
        "unassigned": 0,
        "service": 196200,
        "duration": 12400,
        "waiting_time": 237145,
        "priority": 3,
        "distance": 109272,
        "computing_times": {
            "loading": 37,
            "solving": 61,
            "routing": 11
        }
    },
    "unassigned": [],
    "routes": [
        {
            "vehicle": 1,
            "cost": 12400,
            "service": 196200,
            "duration": 12400,
            "waiting_time": 237145,
            "priority": 3,
            "distance": 109272,
            "steps": [
                {
                    "type": "start",
                    "location": [
                        106.5983012,
                        10.8879148
                    ],
                    "arrival": 1685956255,
                    "duration": 0,
                    "distance": 0
                }, 
                /// More object will response here
                {
                    "type": "break",
                    "id": 6000,
                    "service": 3600,
                    "waiting_time": 177741,
                    "arrival": 1686220659,
                    "duration": 12400,
                    "distance": 109272
                },
                {
                    "type": "end",
                    "location": [
                        106.5983012,
                        10.8879148
                    ],
                    "arrival": 1686402000,
                    "duration": 12400,
                    "distance": 109272
                }
            ],
            "geometry": 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        }
    ]
}

Response body description¶

Parameter	Type	Description
code	number	Status code of the response. `0` indicates the problem was solved successfully.
summary	object	Aggregated metrics across all routes in the solution.
summary.cost	number	Total cost of the solution (the objective value the solver minimizes, derived mainly from travel time).
summary.unassigned	number	Number of jobs that could not be assigned to any vehicle.
summary.service	number	Total service time spent at all visited jobs, in seconds.
summary.duration	number	Total travel (driving) time across all routes, in seconds.
summary.waiting_time	number	Total time vehicles spend waiting for time windows to open, in seconds.
summary.priority	number	Sum of the `priority` values of all assigned jobs.
summary.distance	number	Total distance covered by all routes, in meters.
summary.computing_times	object	Time the solver spent in each phase, in milliseconds.
summary.computing_times.loading	number	Time spent loading and preparing the input, in milliseconds.
summary.computing_times.solving	number	Time spent optimizing the routes, in milliseconds.
summary.computing_times.routing	number	Time spent computing the route geometries, in milliseconds.
unassigned	array	List of jobs that could not be served, with their `id` and `location`. Empty when every job is assigned.
routes	array	One entry per vehicle that is used in the solution.
routes[].vehicle	number	`id` of the vehicle that performs this route.
routes[].cost	number	Cost contribution of this route to `summary.cost`.
routes[].service	number	Total service time at the jobs on this route, in seconds.
routes[].duration	number	Total travel (driving) time of this route, in seconds.
routes[].waiting_time	number	Time the vehicle waits for time windows on this route, in seconds.
routes[].priority	number	Sum of the `priority` values of the jobs on this route.
routes[].distance	number	Distance covered by this route, in meters.
routes[].steps	array	Ordered list of stops the vehicle makes along the route.
routes[].steps[].type	string	Type of the step: `start`, `job`, `pickup`, `delivery`, `break`, or `end`.
routes[].steps[].id	number	`id` of the job or break this step refers to (present for `job`, `pickup`, `delivery` and `break` steps).
routes[].steps[].location	array	Coordinates of the step, in `[longitude, latitude]` order (present for `start`, `end` and job steps).
routes[].steps[].service	number	Service or break duration at this step, in seconds.
routes[].steps[].waiting_time	number	Time the vehicle waits at this step before service can start, in seconds.
routes[].steps[].arrival	number	Time the vehicle arrives at this step, in seconds (relative to the planning horizon or as a Unix timestamp, matching the input `time_windows`).
routes[].steps[].duration	number	Cumulative travel time from the start of the route up to this step, in seconds.
routes[].steps[].distance	number	Cumulative distance from the start of the route up to this step, in meters.
routes[].geometry	string	Full route geometry as a `google polyline 5` encoded string.