shortest-path

To find the shortest path in a weighted graph, you can use algorithms like Dijkstra for non-negative weights, Bellman-Ford for negative weights, Floyd-Warshall for all-pairs, or A* for heuristic geographic searches. This Skill implements these with path reconstruction for logistics and network optimization.

Yes, you can compute all-pairs shortest paths for dense graphs or precomputed matrices using the Floyd-Warshall algorithm. This Skill provides Floyd-Warshall implementation to generate complete distance matrices for comprehensive network analysis.

You handle negative weights and detect negative cycles using the Bellman-Ford algorithm. This Skill includes Bellman-Ford with robust path reconstruction and optional negative-cycle detection to ensure safe routing in complex networks.

The best way to compute single-source shortest paths with non-negative edge weights is using Dijkstra's algorithm. This Skill implements Dijkstra to efficiently find optimal routes and connectivity for transportation networks.

Yes, A* search works for geographic distance routing when an admissible heuristic is available. This Skill implements A* to enable heuristic search, optimizing pathfinding in real-world scenarios like city logistics and emergency response planning.

You reconstruct the actual path by calling the dijkstra or bellman_ford functions to obtain distances and using the built-in path reconstruction features. This Skill provides robust path reconstruction alongside distance calculations for all implemented algorithms.