# vrp_vroomShipments - Experimental¶

vrp_vroomShipments - Vehicle Routing Problem with VROOM, involving only shipments.

Warning

Possible server crash

• These functions might create a server crash

Warning

Experimental functions

• They are not officially of the current release.

• They likely will not be officially be part of the next release:

• The functions might not make use of ANY-INTEGER and ANY-NUMERICAL

• Name might change.

• Signature might change.

• Functionality might change.

• pgTap tests might be missing.

• Might need c/c++ coding.

• May lack documentation.

• Documentation if any might need to be rewritten.

• Documentation examples might need to be automatically generated.

• Might need a lot of feedback from the comunity.

• Might depend on a proposed function of vrpRouting

• Might depend on a deprecated function of vrpRouting

Availability

Version 0.3.0

• Function modified for VROOM 1.11.0

Version 0.2.0

• New experimental function

## Description¶

VROOM is an open-source optimization engine that aims at providing good solutions to various real-life vehicle routing problems (VRP) within a small computing time. This function can be used to get the solution to a problem involving only shipments.

## Signature¶

Summary

vrp_vroomShipments(
Shipments SQL, Shipments Time Windows SQL,
Vehicles SQL, Breaks SQL, Breaks Time Windows SQL,
Matrix SQL [, exploration_level] [, timeout])  -- Experimental on v0.2

RETURNS SET OF
(seq, vehicle_seq, vehicle_id, vehicle_data, step_seq, step_type, task_id,


Optional parameters are named parameters and have a default value.

Using defaults

vrp_vroomShipments(
Shipments SQL, Shipments Time Windows SQL,
Vehicles SQL, Breaks SQL, Breaks Time Windows SQL,
Matrix SQL)

RETURNS SET OF
(seq, vehicle_seq, vehicle_id, vehicle_data, step_seq, step_type, task_id,


Example: This example is based on the modified VROOM Data of the Sample Data network. The modification in the tables is mentioned at the end of the Sample Data.

SELECT *
FROM vrp_vroomShipments(
'SELECT * FROM vroom.shipments',
'SELECT * FROM vroom.shipments_time_windows',
'SELECT * FROM vroom.vehicles',
'SELECT * FROM vroom.breaks',
'SELECT * FROM vroom.breaks_time_windows',
'SELECT * FROM vroom.matrix'
);
seq | vehicle_seq | vehicle_id | vehicle_data | step_seq | step_type | task_id | location_id | task_data |       arrival       | travel_time | setup_time | service_time | waiting_time |      departure      | load
-----+-------------+------------+--------------+----------+-----------+---------+-------------+-----------+---------------------+-------------+------------+--------------+--------------+---------------------+------
1 |           1 |          1 | {}           |        1 |         1 |      -1 |           1 | {}        | 2021-09-02 09:05:00 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 09:05:00 | {0}
2 |           1 |          1 | {}           |        2 |         5 |       1 |           1 | {}        | 2021-09-02 09:05:00 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 09:05:00 | {0}
3 |           1 |          1 | {}           |        3 |         3 |       4 |           1 | {}        | 2021-09-02 09:05:00 | 00:00:00    | 00:00:00   | 00:37:30     | 01:41:15     | 2021-09-02 11:23:45 | {20}
4 |           1 |          1 | {}           |        4 |         4 |       4 |           4 | {}        | 2021-09-02 11:25:00 | 00:01:15    | 00:00:00   | 00:37:30     | 00:03:45     | 2021-09-02 12:06:15 | {0}
5 |           1 |          1 | {}           |        5 |         3 |       5 |           2 | {}        | 2021-09-02 12:07:45 | 00:01:30    | 00:00:00   | 00:37:30     | 00:34:45     | 2021-09-02 13:20:00 | {10}
6 |           1 |          1 | {}           |        6 |         3 |       3 |           1 | {}        | 2021-09-02 13:20:50 | 00:00:50    | 00:00:00   | 00:37:30     | 00:00:00     | 2021-09-02 13:58:20 | {30}
7 |           1 |          1 | {}           |        7 |         4 |       5 |           2 | {}        | 2021-09-02 13:59:10 | 00:00:50    | 00:00:00   | 00:37:30     | 00:03:45     | 2021-09-02 14:40:25 | {20}
8 |           1 |          1 | {}           |        8 |         4 |       3 |           2 | {}        | 2021-09-02 14:40:25 | 00:00:00    | 00:00:00   | 00:37:30     | 00:03:20     | 2021-09-02 15:21:15 | {0}
9 |           1 |          1 | {}           |        9 |         6 |      -1 |           1 | {}        | 2021-09-02 15:22:05 | 00:00:50    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 15:22:05 | {0}
10 |           1 |          1 | {}           |        0 |         0 |       0 |           0 | {}        | 1970-01-01 00:00:00 | 00:05:15    | 00:00:00   | 03:45:00     | 02:26:50     | 1970-01-01 00:00:00 | {}
11 |           2 |          4 | {}           |        1 |         1 |      -1 |           3 | {}        | 2021-09-02 09:04:10 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 09:04:10 | {0}
12 |           2 |          4 | {}           |        2 |         5 |       4 |           1 | {}        | 2021-09-02 09:04:10 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 09:04:10 | {0}
13 |           2 |          4 | {}           |        3 |         3 |       2 |           5 | {}        | 2021-09-02 09:04:35 | 00:00:25    | 00:00:00   | 00:37:30     | 00:01:40     | 2021-09-02 09:43:45 | {10}
14 |           2 |          4 | {}           |        4 |         3 |       1 |           3 | {}        | 2021-09-02 09:44:10 | 00:00:25    | 00:00:00   | 00:37:30     | 00:00:00     | 2021-09-02 10:21:40 | {20}
15 |           2 |          4 | {}           |        5 |         4 |       2 |           6 | {}        | 2021-09-02 10:23:10 | 00:01:30    | 00:00:00   | 00:37:30     | 00:00:00     | 2021-09-02 11:00:40 | {10}
16 |           2 |          4 | {}           |        6 |         4 |       1 |           5 | {}        | 2021-09-02 11:02:31 | 00:01:51    | 00:00:00   | 00:37:30     | 04:52:54     | 2021-09-02 16:32:55 | {0}
17 |           2 |          4 | {}           |        7 |         6 |      -1 |           3 | {}        | 2021-09-02 16:33:20 | 00:00:25    | 00:00:00   | 00:00:00     | 00:00:00     | 2021-09-02 16:33:20 | {0}
18 |           2 |          4 | {}           |        0 |         0 |       0 |           0 | {}        | 1970-01-01 00:00:00 | 00:04:36    | 00:00:00   | 02:30:00     | 04:54:34     | 1970-01-01 00:00:00 | {}
19 |           0 |          0 | {}           |        0 |         0 |       0 |           0 | {}        | 1970-01-01 00:00:00 | 00:09:51    | 00:00:00   | 06:15:00     | 07:21:24     | 1970-01-01 00:00:00 | {}
(19 rows)



## Parameters¶

Parameter

Type

Description

Shipments SQL

TEXT

Shipments SQL query describing pickup and delivery tasks that should happen within same route.

Shipments Time Windows SQL

TEXT

Time Windows SQL query describing valid slots for pickup and delivery service start.

Vehicles SQL

TEXT

Vehicles SQL query describing the available vehicles.

Breaks SQL

TEXT

Breaks SQL query describing the driver breaks.

Breaks Time Windows SQL

TEXT

Time Windows SQL query describing valid slots for break start.

Matrix SQL

TEXT

Time Matrix SQL query containing the distance or travel times between the locations.

### Optional Parameters¶

Parameter

Type

Default

Description

exploration_level

INTEGER

$$5$$

Exploration level to use while solving.

• Ranges from [0, 5]

• A smaller exploration level gives faster result.

timeout

INTERVAL

‘-00:00:01’::INTERVAL

Timeout value to stop the solving process.

• Gives the best possible solution within a time limit. Note that some additional seconds may be required to return back the data.

• Any negative timeout value is ignored.

## Inner Queries¶

### Shipments SQL¶

A SELECT statement that returns the following columns:

id, p_location_id [, p_setup, p_service], d_location_id [, d_setup, d_service]
[, amount, skills, priority, p_data, d_data]


Column

Type

Default

Description

id

ANY-INTEGER

Positive unique identifier of the shipment.

p_location_id

ANY-INTEGER

Positive identifier of the pickup location.

p_setup

INTERVAL

‘00:00:00’::INTERVAL

Pickup setup duration.

p_service

INTERVAL

‘00:00:00’::INTERVAL

Pickup service duration.

d_location_id

ANY-INTEGER

Positive identifier of the delivery location.

d_setup

INTERVAL

‘00:00:00’::INTERVAL

Delivery setup duration.

d_service

INTERVAL

‘00:00:00’::INTERVAL

Delivery service duration.

amount

ARRAY[ANY-INTEGER]

Empty Array

Array of non-negative integers describing multidimensional quantities such as number of items, weight, volume etc.

• All shipments must have the same value of array_length(amount, 1)

skills

ARRAY[INTEGER]

Empty Array

Array of non-negative integers defining mandatory skills.

priority

INTEGER

0

Priority level of the shipment.

• Ranges from [0, 100]

p_data

JSONB

‘{}’::JSONB

Any metadata information of the pickup shipment.

d_data

JSONB

‘{}’::JSONB

Any metadata information of the delivery shipment.

Where:

ANY-INTEGER

SMALLINT, INTEGER, BIGINT

### Vehicles SQL¶

A SELECT statement that returns the following columns:

id, start_id, end_id
[, capacity, skills, tw_open, tw_close, speed_factor, max_tasks, data]


Column

Type

Default

Description

id

ANY-INTEGER

Positive unique identifier of the vehicle.

start_id

ANY-INTEGER

Positive identifier of the vehicle start location.

end_id

ANY-INTEGER

Positive identifier of the vehicle end location.

capacity

ARRAY[ANY-INTEGER]

Empty Array

Array of non-negative integers describing multidimensional quantities such as number of items, weight, volume etc.

• All vehicles must have the same value of array_length(capacity, 1)

skills

ARRAY[INTEGER]

Empty Array

Array of non-negative integers defining mandatory skills.

tw_open

TIMESTAMP

‘1970-01-01 00:00:00’::TIMESTAMP

Time window opening time.

tw_close

TIMESTAMP

‘2106-02-07 06:28:15’::TIMESTAMP

Time window closing time.

speed_factor

ANY-NUMERICAL

$$1.0$$

Vehicle travel time multiplier.

• Max value of speed factor for a vehicle shall not be greater than 5 times the speed factor of any other vehicle.

INTEGER

$$2147483647$$

Maximum number of tasks in a route for the vehicle.

• A job, pickup, or delivery is counted as a single task.

data

JSONB

‘{}’::JSONB

Any metadata information of the vehicle.

Note:

• At least one of the start_id or end_id shall be present.

• If end_id is omitted, the resulting route will stop at the last visited task, whose choice is determined by the optimization process.

• If start_id is omitted, the resulting route will start at the first visited task, whose choice is determined by the optimization process.

• To request a round trip, specify both start_id and end_id as the same index.

• A vehicle is only allowed to serve a set of tasks 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.

• tw_open ≤ tw_close

### Breaks SQL¶

A SELECT statement that returns the following columns:

id, vehicle_id [, service, data]


Column

Type

Default

Description

id

ANY-INTEGER

Positive unique identifier of the break. (unique for the same vehicle).

vehicle_id

ANY-INTEGER

Positive unique identifier of the vehicle.

service

INTERVAL

‘00:00:00’::INTERVAL

The break duration.

data

JSONB

‘{}’::JSONB

Any metadata information of the break.

### Time Windows SQL¶

A SELECT statement that returns the following columns:

id [, kind], tw_open, tw_close


Column

Type

Description

id

ANY-INTEGER

Positive unique identifier of the job, pickup/delivery shipment, or break.

kind

CHAR

Only required for shipments time windows. Value in [‘p’, ‘d’] indicating whether the time window is for:

• Pickup shipment, or

• Delivery shipment.

tw_open

TIMESTAMP

Time window opening time.

tw_close

TIMESTAMP

Time window closing time.

Note:

• All timings are in seconds when represented as an INTEGER.

• Every row must satisfy the condition: tw_open ≤ tw_close.

• 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 column are relative to the start of the planning horizon.

• Absolute values, “real” timestamps. In that case all times reported in output with the arrival column can be interpreted as timestamps.

### Time Matrix SQL¶

A SELECT statement that returns the following columns:

start_id, end_id, duration [, cost]


Column

Type

Default

Description

start_id

ANY-INTEGER

Identifier of the start node.

end_id

ANY-INTEGER

Identifier of the end node.

duration

INTERVAL

Time to travel from start_id to end_id

cost

INTEGER

duration

Cost to travel from start_id to end_id

## Result Columns¶

Returns set of

(seq, vehicle_seq, vehicle_id, vehicle_data, step_seq, step_type, task_id,


Column

Type

Description

seq

BIGINT

Sequential value starting from 1.

vehicle_seq

BIGINT

Sequential value starting from 1 for current vehicles. The $$n^{th}$$ vehicle in the solution.

• 0: Summary row for the complete problem

vehicle_id

BIGINT

Current vehicle identifier.

• -1: Vehicle denoting all the unallocated tasks.

• 0: Summary row for the complete problem

vehicle_data

JSONB

step_seq

BIGINT

Sequential value starting from 1 for the stops made by the current vehicle. The $$m^{th}$$ stop of the current vehicle.

• 0: Summary row

step_type

INTEGER

Kind of the step location the vehicle is at:

• 0: Summary row

• 1: Starting location

• 2: Job location

• 3: Pickup location

• 4: Delivery location

• 5: Break location

• 6: Ending location

BIGINT

Identifier of the task performed at this step.

• 0: Summary row

• -1: If the step is starting/ending location.

location_id

BIGINT

• 0: Summary row

JSONB

arrival

TIMESTAMP

Estimated time of arrival at this step.

travel_time

INTERVAL

Travel time from previous step_seq to current step_seq.

• 0: When step_type = 1

setup_time

INTERVAL

Setup time at this step.

service_time

INTERVAL

Service time at this step.

waiting_time

INTERVAL

Waiting time upon arrival at this step.

departure

TIMESTAMP

Estimated time of arrival at this step.

• $$arrival + service\_time + waiting\_time$$.

BIGINT

Vehicle load after step completion (with capacity constraints)

Note:

• Unallocated tasks are mentioned at the end with vehicle_id = -1.

• The last step of every vehicle denotes the summary row, where the columns travel_time, service_time and waiting_time denote the total time for the corresponding vehicle,

• The last row denotes the summary for the complete problem, where the columns travel_time, service_time and waiting_time denote the total time for the complete problem,

Problem involving 1 shipment, using a single vehicle, similar to the VROOM Documentation Example 2 without jobs and with a shipment.

SELECT *
FROM vrp_vroomShipments(
$shipments$
SELECT * FROM (
VALUES (100, 1, 4)
) AS C(id, p_location_id, d_location_id)
$shipments$,
NULL,
$vehicles$
SELECT * FROM (
VALUES (1, 1, 4)
) AS C(id, start_id, end_id)
$vehicles$,
NULL,
NULL,
$matrix$
SELECT start_id, end_id, make_interval(secs => duration) AS duration FROM (
VALUES (1, 2, 2104), (1, 3, 197), (1, 4, 1299),
(2, 1, 2103), (2, 3, 2255), (2, 4, 3152),
(3, 1, 197), (3, 2, 2256), (3, 4, 1102),
(4, 1, 1299), (4, 2, 3153), (4, 3, 1102)
) AS C(start_id, end_id, duration)
$matrix$
);
seq | vehicle_seq | vehicle_id | vehicle_data | step_seq | step_type | task_id | location_id | task_data |       arrival       | travel_time | setup_time | service_time | waiting_time |      departure      | load
-----+-------------+------------+--------------+----------+-----------+---------+-------------+-----------+---------------------+-------------+------------+--------------+--------------+---------------------+------
1 |           1 |          1 | {}           |        1 |         1 |      -1 |           1 | {}        | 1970-01-01 00:00:00 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:00:00 | {}
2 |           1 |          1 | {}           |        2 |         3 |     100 |           1 | {}        | 1970-01-01 00:00:00 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:00:00 | {}
3 |           1 |          1 | {}           |        3 |         4 |     100 |           4 | {}        | 1970-01-01 00:21:39 | 00:21:39    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:21:39 | {}
4 |           1 |          1 | {}           |        4 |         6 |      -1 |           4 | {}        | 1970-01-01 00:21:39 | 00:00:00    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:21:39 | {}
5 |           1 |          1 | {}           |        0 |         0 |       0 |           0 | {}        | 1970-01-01 00:00:00 | 00:21:39    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:00:00 | {}
6 |           0 |          0 | {}           |        0 |         0 |       0 |           0 | {}        | 1970-01-01 00:00:00 | 00:21:39    | 00:00:00   | 00:00:00     | 00:00:00     | 1970-01-01 00:00:00 | {}
(6 rows)