This section describes the Yen’s K-shortest paths algorithm in the Neo4j Graph Algorithms library.
Yen’s K-shortest paths algorithm computes single-source K-shortest loopless paths for a graph with non-negative relationship weights.
This section includes:
Algorithm was defined in 1971 by Jin Y. Yen in the research paper Finding the K Shortest Loopless Paths in a Network. Our implementation uses Dijkstra algorithm to find the shortest path and then proceeds to find k-1 deviations of the shortest paths.
Yen’s K-Shortest paths algorithm does not support negative weights. The algorithm assumes that adding a relationship to a path can never make a path shorter - an invariant that would be violated with negative weights.
The following will create a sample graph:
MERGE (a:Loc {name:'A'})
MERGE (b:Loc {name:'B'})
MERGE (c:Loc {name:'C'})
MERGE (d:Loc {name:'D'})
MERGE (e:Loc {name:'E'})
MERGE (f:Loc {name:'F'})
MERGE (a)-[:ROAD {cost:50}]->(b)
MERGE (a)-[:ROAD {cost:50}]->(c)
MERGE (a)-[:ROAD {cost:100}]->(d)
MERGE (b)-[:ROAD {cost:40}]->(d)
MERGE (c)-[:ROAD {cost:40}]->(d)
MERGE (c)-[:ROAD {cost:80}]->(e)
MERGE (d)-[:ROAD {cost:30}]->(e)
MERGE (d)-[:ROAD {cost:80}]->(f)
MERGE (e)-[:ROAD {cost:40}]->(f);
The following will run the algorithm and stream results:
MATCH (start:Loc{name:'A'}), (end:Loc{name:'F'})
CALL algo.kShortestPaths.stream(start, end, 3, 'cost' ,{})
YIELD index, nodeIds, costs
RETURN [node in algo.getNodesById(nodeIds) | node.name] AS places,
costs,
reduce(acc = 0.0, cost in costs | acc + cost) AS totalCost
places |
costs |
totalCost |
---|---|---|
["A", "B", "D", "E", "F"] |
[50.0, 40.0, 30.0, 40.0] |
160.0 |
["A", "C", "D", "E", "F"] |
[50.0, 40.0, 30.0, 40.0] |
160.0 |
["A", "B", "D", "F"] |
[50.0, 40.0, 80.0] |
170.0 |
This procedure doesn’t return paths by default, but we can have it return those by passing in the config path: true
.
The following will run the algorithm and stream results, including paths:
MATCH (start:Loc{name:'A'}), (end:Loc{name:'F'})
CALL algo.kShortestPaths.stream(start, end, 3, 'cost', {path: true})
YIELD path
RETURN path
LIMIT 1
The following will run the algorithm and write back results:
MATCH (start:Loc{name:'A'}), (end:Loc{name:'F'})
CALL algo.kShortestPaths(start, end, 3, 'cost' ,{})
YIELD resultCount
RETURN resultCount
The following will return all 3 of the shortest path:
MATCH p=()-[r:PATH_0|:PATH_1|:PATH_2]->() RETURN p LIMIT 25
The quickest route takes us from A to B, via D and E and is saved as PATH_0
.
Second quickest path is saved as PATH_1
and third one is saved as`PATH_2`
If label and relationship-type are not selective enough to describe your subgraph to run the algorithm on, you can use Cypher statements to load or project subsets of your graph. This can also be used to run algorithms on a virtual graph. You can learn more in the Section 2.2, “Cypher projection” section of the manual.
Set graph:'cypher'
in the config:
MATCH (start:Loc{name:'A'}), (end:Loc{name:'F'})
CALL algo.kShortestPaths(start, end, 3, 'cost',{
nodeQuery:'MATCH(n:Loc) WHERE not n.name = "C" RETURN id(n) as id',
relationshipQuery:'MATCH (n:Loc)-[r:ROAD]->(m:Loc) RETURN id(n) as source, id(m) as target, r.cost as weight',
graph:'cypher',writePropertyPrefix:'cypher_'})
YIELD resultCount
RETURN resultCount
The following will run the algorithm and write back results:
CALL algo.kShortestPaths(startNode:Node, endNode:Node, k:int, weightProperty:String,
{nodeQuery:'labelName', relationshipQuery:'relationshipName', direction:'OUT', defaultValue:1.0,
maxDepth:42, write:'true', writePropertyPrefix:'PATH_'})
YIELD resultCount, loadMillis, evalMillis, writeMillis
Name | Type | Default | Optional | Description |
---|---|---|---|---|
startNode |
node |
null |
no |
The start node |
endNode |
node |
null |
no |
The end node |
weightProperty |
string |
null |
yes |
The property name that contains weight. If null, treats the graph as unweighted. Must be numeric. |
nodeQuery |
string |
null |
yes |
The label to load from the graph. If null, load all nodes |
relationshipQuery |
string |
null |
yes |
The relationship-type to load from the graph. If null, load all nodes |
direction |
string |
both |
yes |
The relationship direction to load from the graph. If 'both', treats the relationships as undirected |
defaultValue |
float |
null |
yes |
The default value of the weight in case it is missing or invalid |
maxDepth |
int |
Integer.MAX |
yes |
The depth of the shortest paths traversal |
write |
boolean |
true |
yes |
Specifies if the result should be written back as a node property |
writePropertyPrefix |
string |
'PATH_' |
yes |
The relationship-type prefix written back to the graph |
Name | Type | Description |
---|---|---|
resultCount |
int |
The number of shortest paths results |
loadMillis |
int |
Milliseconds for loading data |
evalMillis |
int |
Milliseconds for running the algorithm |
writeMillis |
int |
Milliseconds for writing result data back |
The Shortest Path algorithms support the following graph types:
✓ directed, unweighted:
✓ directed, weighted
✓ undirected, unweighted
✓ undirected, weighted
algo.kShortestPaths