• Documentation → vrpRouting v0

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VROOM - Category (Experimental)

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

Contents

• VROOM - Category (Experimental)

  • Synopsis

    • Characteristics

    • Terminologies

  • Inner Queries

    • Jobs SQL

    • Shipments SQL

    • Vehicles SQL

    • Breaks SQL

    • Time Windows SQL

    • Time Matrix SQL

  • Result Columns

  • See Also

Functions

• vrp_vroom - Experimental
• vrp_vroomJobs - Experimental
• vrp_vroomShipments - Experimental

Synopsis

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.

VROOM can solve several well-known types of vehicle routing problems (VRP).

• TSP (travelling salesman problem)

• CVRP (capacitated VRP)

• VRPTW (VRP with time windows)

• MDHVRPTW (multi-depot heterogeneous vehicle VRPTW)

• PDPTW (pickup-and-delivery problem with TW)

VROOM can also solve any mix of the above problem types.

Characteristics

VROOM models a Vehicle Routing Problem with vehicles, jobs and shipments.

The vehicles denote the resources that pick and/or deliver the jobs and shipments. They are characterised by:

• Capacity on arbitrary number of metrics

• Skills

• Working hours

• Driver breaks

• Start and end defined on a per-vehicle basis

• Start and end can be different

• Open trip optimization (only start or only end defined)

The jobs denote the single-location pickup and/or delivery tasks, and the shipments denote the pickup-and-delivery tasks that should happen within the same route. They are characterised by:

• Delivery/pickup amounts on arbitrary number of metrics

• Service time windows

• Service duration

• Skills

• Priority

Terminologies

• Tasks: Either jobs or shipments are referred to as tasks.

• Skills: Every task and vehicle may have some set of skills. A task can be served by only that vehicle which has all the skills of the task.

• Priority: Tasks may have some priority assigned, which is useful when all tasks cannot be performed due to constraints, so the tasks with low priority are left unassigned.

• Amount (for shipment), Pickup and delivery (for job): They denote the multidimensional quantities such as number of items, weights, volume, etc.

• Capacity (for vehicle): Every vehicle may have some capacity, denoting the multidimensional quantities. A vehicle can serve only those sets of tasks such that the total sum of the quantity does not exceed the vehicle capacity, at any point of the route.

• Time Window: An interval of time during which some activity can be performed, such as working hours of the vehicle, break of the vehicle, or service start time for a task.

• Break: Array of time windows, denoting valid slots for the break start of a vehicle.

• Service time: The additional time to be spent by a vehicle while serving a task.

• Travel time: The total time the vehicle travels during its route.

• Waiting time: The total time the vehicle is idle, i.e. it is neither traveling nor servicing any task. It is generally the time spent by a vehicle waiting for a task service to open.

Inner Queries

Jobs SQL

A SELECT statement that returns the following columns:

id, location_index
[, service, delivery, pickup, skills, priority]

Column	Type	Default	Description
id	ANY-INTEGER		Non-negative unique identifier of the job.
location_index	ANY-INTEGER		Non-negative identifier of the job location.
service	INTEGER	0	Job service duration, in seconds
delivery	ARRAY[ANY-INTEGER]		Array of non-negative integers describing multidimensional quantities for delivery such as number of items, weight, volume etc. All jobs must have the same value of array_length(delivery, 1)
pickup	ARRAY[ANY-INTEGER]		Array of non-negative integers describing multidimensional quantities for pickup such as number of items, weight, volume etc. All jobs must have the same value of array_length(pickup, 1)
skills	ARRAY[INTEGER]		Array of non-negative integers defining mandatory skills.
priority	INTEGER	0	Priority level of the job Ranges from [0, 100]

Where:

ANY-INTEGER

SMALLINT, INTEGER, BIGINT

Shipments SQL

A SELECT statement that returns the following columns:

id, p_location_index [, p_service], d_location_index [, d_service]
[, amount, skills, priority]

Column	Type	Default	Description
id	ANY-INTEGER		Non-negative unique identifier of the shipment.
p_location_index	ANY-INTEGER		Non-negative identifier of the pickup location.
p_service	INTEGER	0	Pickup service duration, in seconds
d_location_index	ANY-INTEGER		Non-negative identifier of the delivery location.
d_service	INTEGER	0	Delivery service duration, in seconds
amount	ARRAY[ANY-INTEGER]		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]		Array of non-negative integers defining mandatory skills.
priority	INTEGER	0	Priority level of the shipment. Ranges from [0, 100]

Where:

ANY-INTEGER

SMALLINT, INTEGER, BIGINT

Vehicles SQL

A SELECT statement that returns the following columns:

id, start_index, end_index
[, capacity, skills, tw_open, tw_close, speed_factor]

Column	Type	Description
id	ANY-INTEGER	Non-negative unique identifier of the job.
start_index	ANY-INTEGER	Non-negative identifier of the vehicle start location.
end_index	ANY-INTEGER	Non-negative identifier of the vehicle end location.
capacity	ARRAY[ANY-INTEGER]	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]	Array of non-negative integers defining mandatory skills.
tw_open	INTEGER	Time window opening time.
tw_close	INTEGER	Time window closing time.
speed_factor	ANY-NUMERICAL	Vehicle travel time multiplier.

Note:

• At least one of the start_index or end_index shall be present.

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

• If start_index 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_index and end_index 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]

Column	Type	Default	Description
id	ANY-INTEGER		Non-negative unique identifier of the break. (unique for the same vehicle).
vehicle_id	ANY-INTEGER		Non-negative unique identifier of the vehicle.
service	INTEGER	0	The break duration, in seconds

Time Windows SQL

A SELECT statement that returns the following columns:

id [, kind], tw_open, tw_close

Column	Type	Description
id	ANY-INTEGER	Non-negative unique identifier of the job, pickup/delivery shipment, or break.
kind	CHAR	Only required for shipments. Value in [‘p’, ‘d’] indicating whether the time window is for: Pickup shipment, or Delivery shipment.
tw_open	INTEGER	Time window opening time.
tw_close	INTEGER	Time window closing time.

Note:

• All timing are in seconds.

• 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_index, end_index, agg_cost

Column	Type	Description
start_vid	ANY-INTEGER	Identifier of the start node.
end_vid	ANY-INTEGER	Identifier of the end node.
agg_cost	INTEGER	Time to travel from start_vid to end_vid

Result Columns

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.
vehicle_id	BIGINT	Current vehicle identifier.
step_seq	BIGINT	Sequential value starting from 1 for the stops made by the current vehicle. The \(m^{th}\) stop of the current vehicle.
step_type	INTEGER	Kind of the step location the vehicle is at: 1: Starting location 2: Job location 3: Pickup location 4: Delivery location 5: Break location 6: Ending location
task_id	BIGINT	Identifier of the task performed at this step. -1: If the step is starting/ending location.
arrival	INTEGER	Estimated time of arrival at this step, in seconds.
travel_time	INTEGER	Cumulated travel time upon arrival at this step, in seconds
service_time	INTEGER	Service time at this step, in seconds
waiting_time	INTEGER	Waiting time upon arrival at this step, in seconds.
load	BIGINT	Vehicle load after step completion (with capacity constraints)

See Also

• Wikipedia: Vehicle Routing problems

• VROOM: Vehicle Routing Open-source Optimization Machine

• VROOM API Documentation

Indices and tables

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