Dijkstra Shortest Path Calculator
Find shortest paths from a start node over non-negative weighted directed edges given as [from, to, weight] rows.
Description
Find shortest paths from a start node over non-negative weighted directed edges given as [from, to, weight] rows.
Dijkstra Shortest Path Calculator is a focused tool for the following task. Find shortest paths from a start node over non-negative weighted directed edges given as [from, to, weight] rows. It reports Distances, Path, Total cost from the values you provide rather than inventing measurements, coefficients, or professional judgment that are not part of the input.
When to use Dijkstra Shortest Path
Use this graph algorithm when node identity, edge direction, edge weights, traversal ordering, and reachability semantics match the supplied representation.
- Node count
- Required integer. Number of nodes; nodes are indices 0..nodeCount-1.
- Edges
- Optional list. Directed edges as [from, to, weight] rows with non-negative weights.
- Start node
- Optional integer. Start node index.
- End node
- Optional integer. Target node index; omit to compute distances only.
The cited overview of Graph theory supplies background for the terminology and domain context used by this tool.1
How Dijkstra Shortest Path works
Find shortest paths from a start node over non-negative weighted directed edges given as [from, to, weight] rows. Inputs are interpreted exactly in the displayed units and the calculation returns the following fields without presentation rounding.
- Distances
- Returned list. Shortest distance per node; -1 marks unreachable nodes.
- Path
- Returned list. Node indices along the shortest path from start to end; empty when end is omitted.
- Total cost
- Returned number. Total path cost; -1 when end is omitted.
Limitations and assumptions
- Invalid weights, duplicate edges, disconnected components, cycles, tie-breaking, and graph size can change correctness, determinism, or resource use depending on the algorithm.
- Use finite inputs in the displayed units, preserve source measurements and assumptions, and independently verify consequential decisions.
Alternative or Complementary approaches
Visualize and test a small graph with known answers, then use a mature graph library when scale, negative weights, persistence, or advanced diagnostics matter.
References
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Graph theory — Wikipedia contributors
Similar or alternative tools
- Graph Breadth-First Traversal
Visit every node reachable from a start node in breadth-first order over directed edges, visiting neighbors in ascending order and reporting each node's depth.
- Graph Depth-First Traversal
Visit every node reachable from a start node in iterative depth-first preorder over directed edges, descending into the smallest-numbered neighbor first and reporting each node's depth.
- Shortest Unweighted Path Finder
Breadth-first shortest path between two nodes of an unweighted graph given as an adjacency map; reports the hop count and node sequence, or no path.