shortest-path

What problem does it solve?

This Skill helps users compute optimal routes and connectivity in weighted graphs, eliminating manual graph-traversal tasks and enabling rapid decision-making in routing, logistics, and network analysis.

Core Features & Use Cases

• Single-source shortest paths with non-negative weights using Dijkstra.
• All-pairs shortest paths with Floyd-Warshall for dense graphs or precomputed matrices.
• Negative weights handling via Bellman-Ford and robust path reconstruction.
• Heuristic search using A* when an admissible heuristic is available (e.g., geographic distance).
• Real-world scenarios: city logistics routing, emergency response planning, network routing optimization.

Quick Start

Run the included examples to compute a sample path, or adapt the code to your graph. For example, use networkx to build a graph and call the dijkstra, bellman_ford, floyd_warshall, or a_star functions to obtain distances and reconstruct paths.