Dijkstra's Shortest-Path Algorithm: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
|||
| Line 1: | Line 1: | ||
=External= | |||
* https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/rxrPa/dijkstras-shortest-path-algorithm | |||
* https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/iIzo8/heaps-operations-and-applications | |||
=Internal= | =Internal= | ||
* [[Shortest Path in a Graph]] | * [[Shortest Path in a Graph]] | ||
Revision as of 20:01, 14 October 2021
External
- https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/rxrPa/dijkstras-shortest-path-algorithm
- https://www.coursera.org/learn/algorithms-graphs-data-structures/lecture/iIzo8/heaps-operations-and-applications
Internal
Overview
The Problem
The single-source shortest paths is formally defined as follows: given a directed graph G=(V, E) , with n = │V│ and m=│E│, where each edge e has a non-negative length ℓe, and a source vertex s, compute for each v ∈ V the length L(v) of the shortest path s → v.
The assumption that the length is non-negative is important. Dijkstra's shortest-path algorithm does not work correctly in presence of negative length edges.
Speed Up
The Dijkstra's algorithm can be speed up with the use of a heap.