Compare shortest-path algorithms side-by-side on Cairo's transportation network. Select algorithms, pick source and target nodes, and watch them race.
15 neighborhoods and 10 facilities connected by 28 bidirectional roads.
Select which algorithms to compare, then pick source and target nodes to see them find the shortest path.
TensorFlow.js neural network trained on temporal traffic data to forecast congestion levels.
Theoretical complexity vs actual performance on the Cairo network.
| Algorithm | Complexity | Description | Best For |
|---|---|---|---|
| Dijkstra (Array) | O(V²) | Linear search priority queue | Very small graphs |
| Dijkstra (Heap) | O((V+E) log V) | Binary heap priority queue | Sparse graphs |
| A* Search | O((V+E) log V) | Haversine heuristic guidance | Point-to-point |
| Bellman-Ford | O(V·E) | Dynamic programming relaxation | Negative weights |
| Floyd-Warshall | O(V³) | All-pairs distance matrix | All-pairs (small V) |