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Comparing Dijkstra's & Floyd's Algorithms Simplified Revision Notes

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10.4.3 Comparing Dijkstra's & Floyd's Algorithms

Dijkstra's and Floyd's algorithms are both used to find shortest paths in a graph, but they differ in purpose, approach, and application. Understanding these differences can help determine which algorithm to use in a given scenario.

Key Differences

Purpose

  • Dijkstra's Algorithm: Finds the shortest path from a single source node to all other nodes in the graph.
  • Floyd's Algorithm: Finds the shortest paths between all pairs of nodes in the graph.

Approach

  • Dijkstra's Algorithm: Uses a greedy approach, iteratively selecting the closest unvisited node and updating its neighbours' distances.
  • Floyd's Algorithm: Uses a dynamic programming approach, iteratively considering each node as an intermediate step to update the shortest paths between all pairs.

Graph Type

  • Both algorithms work on directed and undirected graphs, provided there are no negative weight cycles. However, Dijkstra's is more sensitive to negative edge weights.

Use Cases

  • Use Dijkstra's for routing from a single source, such as navigation or network routing.
  • Use Floyd's for analysing the shortest paths between multiple nodes, such as transportation networks or communication analysis.

Note Summary

infoNote

Common Mistakes

  1. Confusing the Purposes: Using Floyd's algorithm when only a single-source shortest path is required, or Dijkstra's when all-pairs shortest paths are needed.
  2. Applying to Graphs with Negative Cycles: Neither algorithm can handle graphs with negative weight cycles.
  3. Inefficient Use: Applying Dijkstra's algorithm repeatedly for all-pairs shortest paths instead of using Floyd's, leading to unnecessary computation.
  4. Ignoring Edge Weights: Treating edges as unweighted in problems where weights are critical to the solution.
infoNote

Key Formulas/Theorems

  1. Dijkstra's Tentative Distance Update:
d[u]=min(d[u],d[v]+weight of edge (v,u))d[u] = \min(d[u], d[v] + \text{weight of edge } (v, u))
  1. Floyd's Distance Update:
d[i][j]=min(d[i][j],d[i][k]+d[k][j])d[i][j] = \min(d[i][j], d[i][k] + d[k][j])
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