pgr_TSP¶
pgr_TSP
- Aproximation using metric algorithm.
Availability:
Version 3.2.1
Metric Algorithm from Boost library
Simulated Annealing Algorithm no longer supported
The Simulated Annealing Algorithm related parameters are ignored: max_processing_time, tries_per_temperature, max_changes_per_temperature, max_consecutive_non_changes, initial_temperature, final_temperature, cooling_factor, randomize
Version 2.3.0
Signature change
Old signature no longer supported
Version 2.0.0
Official function
Description¶
Problem Definition¶
The travelling salesperson problem (TSP) asks the following question:
Given a list of cities and the distances between each pair of cities, which is the shortest possible route that visits each city exactly once and returns to the origin city?
General Characteristics¶
This problem is an NP-hard optimization problem.
Metric Algorithm is used
Implementation generates solutions that are twice as long as the optimal tour in the worst case when:
Graph is undirected
Graph is fully connected
Graph where traveling costs on edges obey the triangle inequality.
On an undirected graph:
The traveling costs are symmetric:
Traveling costs from
u
tov
are just as much as traveling fromv
tou
Characteristics¶
Can be Used with Cost Matrix - Category functions preferably with directed => false.
With
directed => false
Will generate a graph that:
is undirected
is fully connected (As long as the graph has one component)
all traveling costs on edges obey the triangle inequality.
When
start_vid = 0 OR end_vid = 0
The solutions generated is garanteed to be twice as long as the optimal tour in the worst case
When
start_vid != 0 AND end_vid != 0 AND start_vid != end_vid
It is not garanteed that the solution will be, in the worse case, twice as long as the optimal tour, due to the fact that end_vid is forced to be in a fixed position.
With
directed => true
It is not garanteed that the solution will be, in the worse case, twice as long as the optimal tour
Will generate a graph that:
is directed
is fully connected (As long as the graph has one component)
some (or all) traveling costs on edges might not obey the triangle inequality.
As an undirected graph is required, the directed graph is transformed as follows:
edges (u, v) and (v, u) is considered to be the same edge (denoted (u, v)
if
agg_cost
differs between one or more instances of edge (u, v)The minimum value of the
agg_cost
all instances of edge (u, v) is going to be considered as theagg_cost
of edge (u, v)Some (or all) traveling costs on edges will still might not obey the triangle inequality.
When the data is incomplete, but it is a connected graph, the missing values will be calculated with dijkstra algorithm.
Signatures¶
Summary
pgr_TSP(Matrix SQL, [start_id], [end_id])
RETURNS SETOF (seq, node, cost, agg_cost)
Example: Using pgr_dijkstraCostMatrix to generate the matrix information
Line 5 Vertices 15 to 18 are not included because they are not connected.
1SELECT * FROM pgr_TSP(
2 $$
3 SELECT * FROM pgr_dijkstraCostMatrix(
4 'SELECT id, source, target, cost, reverse_cost FROM edge_table',
5 (SELECT array_agg(id) FROM edge_table_vertices_pgr WHERE id < 14),
6 directed => false)
7 $$);
8 seq | node | cost | agg_cost
9-----+------+------+----------
10 1 | 1 | 0 | 0
11 2 | 2 | 1 | 1
12 3 | 3 | 1 | 2
13 4 | 4 | 1 | 3
14 5 | 9 | 1 | 4
15 6 | 12 | 1 | 5
16 7 | 6 | 2 | 7
17 8 | 5 | 1 | 8
18 9 | 8 | 1 | 9
19 10 | 7 | 1 | 10
20 11 | 10 | 3 | 13
21 12 | 11 | 1 | 14
22 13 | 13 | 2 | 16
23 14 | 1 | 4 | 20
24(14 rows)
25
Parameters¶
Parameter |
Type |
Default |
Description |
---|---|---|---|
Matrix SQL |
|
An SQL query, described in the Matrix SQL section. |
|
start_vid |
|
|
The first visiting vertex
|
end_vid |
|
|
Last visiting vertex before returning to
|
Inner query¶
Matrix SQL¶
Matrix SQL: an SQL query, which should return a set of rows with the following columns:
Column |
Type |
Description |
---|---|---|
start_vid |
|
Identifier of the starting vertex. |
end_vid |
|
Identifier of the ending vertex. |
agg_cost |
|
Cost for going from start_vid to end_vid |
Result Columns¶
Returns SET OF (seq, node, cost, agg_cost)
Column |
Type |
Description |
---|---|---|
seq |
|
Row sequence. |
node |
|
Identifier of the node/coordinate/point. |
cost |
|
Cost to traverse from the current
|
agg_cost |
|
Aggregate cost from the
|
Additional Examples¶
- Example
Start from vertex \(7\)
Line 9
start_vid => 7
1SELECT * FROM pgr_TSP(
2 $$
3 SELECT * FROM pgr_dijkstraCostMatrix(
4 'SELECT id, source, target, cost, reverse_cost FROM edge_table',
5 (SELECT array_agg(id) FROM edge_table_vertices_pgr WHERE id < 14),
6 directed => false
7 )
8 $$,
9 start_id => 7
10);
11 seq | node | cost | agg_cost
12-----+------+------+----------
13 1 | 7 | 0 | 0
14 2 | 8 | 1 | 1
15 3 | 5 | 1 | 2
16 4 | 2 | 1 | 3
17 5 | 1 | 1 | 4
18 6 | 3 | 2 | 6
19 7 | 4 | 1 | 7
20 8 | 9 | 1 | 8
21 9 | 12 | 1 | 9
22 10 | 11 | 1 | 10
23 11 | 6 | 1 | 11
24 12 | 10 | 2 | 13
25 13 | 13 | 1 | 14
26 14 | 7 | 4 | 18
27(14 rows)
28
- Example
Using points of interest to generate an asymetric matrix.
To generate an asymmetric matrix:
Line 5 The
side
information of pointsOfInterset is ignored by not including it in the queryLine 7 Generating an asymetric matrix with
directed => true
\(min(agg\_cost(u, v), agg\_cost(v, u))\) is going to be considered as the
agg_cost
The solution that can be larger than twice as long as the optimal tour because:
Triangle inequality might not be satisfied.
start_id != 0 AND end_id != 0
1SELECT * FROM pgr_TSP(
2 $$
3 SELECT * FROM pgr_withPointsCostMatrix(
4 'SELECT id, source, target, cost, reverse_cost FROM edge_table ORDER BY id',
5 'SELECT pid, edge_id, fraction from pointsOfInterest',
6 array[-1, 3, 5, 6, -6],
7 directed => true)
8 $$,
9 start_id => 5,
10 end_id => 6
11);
12 seq | node | cost | agg_cost
13-----+------+------+----------
14 1 | 5 | 0 | 0
15 2 | -6 | 0.3 | 0.3
16 3 | -1 | 1.3 | 1.6
17 4 | 3 | 1.6 | 3.2
18 5 | 6 | 1 | 4.2
19 6 | 5 | 1 | 5.2
20(6 rows)
21
- Example
Connected incomplete data
Using selected edges (2, 4, 5, 8, 9, 15) the matrix is not complete but it is connected
1SELECT source AS start_vid, target AS end_vid, 1 AS agg_cost
2FROM edge_table WHERE id IN (2,4,5,8, 9, 15);
3 start_vid | end_vid | agg_cost
4-----------+---------+----------
5 2 | 3 | 1
6 2 | 5 | 1
7 3 | 6 | 1
8 5 | 6 | 1
9 6 | 9 | 1
10 9 | 12 | 1
11(6 rows)
12
Edge (5,12) does not exist on the initial data, but it is calculated internally.
1SELECT * FROM pgr_TSP(
2 $$
3 SELECT source AS start_vid, target AS end_vid, 1 AS agg_cost
4 FROM edge_table
5 WHERE id IN (2,4,5,8,9,15)
6 $$);
7 seq | node | cost | agg_cost
8-----+------+------+----------
9 1 | 2 | 0 | 0
10 2 | 3 | 1 | 1
11 3 | 6 | 1 | 2
12 4 | 12 | 1 | 3
13 5 | 9 | 1 | 4
14 6 | 5 | 1 | 5
15 7 | 2 | 1 | 6
16(7 rows)
17
The queries use the Sample Data network.
See Also¶
Metric Algorithm from Boost library
Indices and tables