From eb6497e805627137e15bf30d3ec46fb510103f56 Mon Sep 17 00:00:00 2001 From: Sadeep Madurange Date: Sun, 2 Nov 2025 14:31:47 +0800 Subject: neo4J post. --- _site/archive/neo4j-a-star-search/index.html | 46 +++++++++++++++------------- 1 file changed, 24 insertions(+), 22 deletions(-) (limited to '_site/archive/neo4j-a-star-search/index.html') diff --git a/_site/archive/neo4j-a-star-search/index.html b/_site/archive/neo4j-a-star-search/index.html index f37d00b..92d350d 100644 --- a/_site/archive/neo4j-a-star-search/index.html +++ b/_site/archive/neo4j-a-star-search/index.html @@ -46,10 +46,26 @@

Back in 2018, we used the Neo4J graph database to track the movement of marine vessels. We were interested in the shortest path a ship could take through a network of about 13,000 route points. -Performance issues with Neo4J’s then-available shortest-path algorithms limited -our search to about 4,000 route points.

+Performance issues with Neo4J’s shortest-path algorithms limited our search to +about 4,000 route points.

-

The fix led to my first contribution to an open-source project:

+

A graph is a finite set of vertices, and a subset of vertex pairs known as +edges. Edges can have weights.

+ +

In the case of vessel tracking, the route points can be modeled as a graph +with the distances between them as weights. For different reasons, people are +interested in minimizing (or maximizing) the weight of a path through a set of +vertices. For instance, we may want to find the shortest path between two +ports.

+ +

Dijkstra’s algorithm is one such algorithm that finds the shortest path between +two vertices. The one drawback of this algorithm is that it computes all the +shortest paths from the source to all other vertices before terminating at the +destination vertex.

+ +

The following enhancement, also known as the A* search, employs spherical +distance between route points (which are on the earth’s surface) as a heuristic +to steer the search in the direction of the destination far more quickly:

package org.neo4j.graphalgo.impl;
 
@@ -327,26 +343,12 @@ public class ShortestPathAStar extends Algorithm<ShortestPathAStar> {
     }
 }
+

The heuristic function is domain-specific. If chosen wisely, it can +significantly speed up the search. In our case, we achieved a 300x speedup, +enabling us to expand our search from 4,000 to 13,000 route points.

-

If you are new to them, a graph is a finite set of vertices (such as ports -ships are known to travel through), and a subset of vertex pairs (such as -origin and destination ports) known as edges.

- -

Edges can have weights. In the case of ships and ports, the weights could be -the distances between ports. For various reasons, people are interested in -minimizing or maximizing the weight of a path through a set of vertices. For -instance, we may want to find the shortest path between two ports.

- -

There’s nothing spectacular about the code. It is, for the most part, a patch -over Dijkstra’s algorithm that employs spherical distance between vertices as a -heuristic to steer the search in the right direction. Dijkstra’s algorithm, on -the other hand, explores all possible paths from the source, which is what -makes it slower.

- -

The heuristic function is domain-specific. I planned to make it configurable, -but didn’t get around to it. With the help of my A* algorithm, we scaled our -search to include all the route points of interest. Here’s a link to -the now-archived official release.

+

The Neo4J graph algorithms open-source project v3.4 shipped +with my implementation of the A* search algorithm.

by Wickramage Don Sadeep Madurange

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