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authorSadeep Madurange <sadeep@asciimx.com>2025-11-02 14:31:47 +0800
committerSadeep Madurange <sadeep@asciimx.com>2025-11-02 14:31:47 +0800
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tree4cb4850480722113b1e79a92283bb0a64c79699e /_site/archive/neo4j-a-star-search
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downloadwww-eb6497e805627137e15bf30d3ec46fb510103f56.tar.gz
neo4J post.
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@@ -46,10 +46,26 @@
<div class="twocol justify"><p>Back in 2018, we used the <a href="https://neo4j.com/" class="external" target="_blank" rel="noopener noreferrer">Neo4J</a> 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.</p>
+Performance issues with Neo4J’s shortest-path algorithms limited our search to
+about 4,000 route points.</p>
-<p>The fix led to my first contribution to an open-source project:</p>
+<p>A graph is a finite set of vertices, and a subset of vertex pairs known as
+edges. Edges can have weights.</p>
+
+<p>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.</p>
+
+<p>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.</p>
+
+<p>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:</p>
<div class="language-plaintext highlighter-rouge"><div class="highlight"><pre class="highlight"><code>package org.neo4j.graphalgo.impl;
@@ -327,26 +343,12 @@ public class ShortestPathAStar extends Algorithm&lt;ShortestPathAStar&gt; {
}
}
</code></pre></div></div>
+<p>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.</p>
-<p>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.</p>
-
-<p>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.</p>
-
-<p>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.</p>
-
-<p>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. <a href="https://github.com/neo4j-contrib/neo4j-graph-algorithms/releases/tag/3.4.0.0" class="external" target="_blank" rel="noopener noreferrer">Here’s</a> a link to
-the now-archived official release.</p>
+<p>The Neo4J graph algorithms open-source project <a href="https://github.com/neo4j-contrib/neo4j-graph-algorithms/releases/tag/3.4.0.0" class="external" target="_blank" rel="noopener noreferrer">v3.4</a> shipped
+with my implementation of the A* search algorithm.</p>
</div>
<p class="post-author right">by Wickramage Don Sadeep Madurange</p>