Floyd-Warshall Algorithm

Floyd-Warshall Algorithm is an algorithm for finding the shortest path between all the pairs of vertices in a weighted graph. This algorithm works for both the directed and undirected weighted graphs. But, it does not work for the graphs with negative cycles (where the sum of the edges in a cycle is negative).

A weighted graph is a graph in which each edge has a numerical value associated with it.

Floyd-Warhshall algorithm is also called as Floyd's algorithm, Roy-Floyd algorithm, Roy-Warshall algorithm, or WFI algorithm.

This algorithm follows the dynamic programming approach to find the shortest paths.

How Floyd-Warshall Algorithm Works?

Let the given graph be:

graph — Initial graph

Follow the steps below to find the shortest path between all the pairs of vertices.

Create a matrix A⁰ of dimension n*n where n is the number of vertices. The row and the column are indexed as i and j respectively. i and j are the vertices of the graph.

Each cell A[i][j] is filled with the distance from the i^th vertex to the j^th vertex. If there is no path from i^th vertex to j^th vertex, the cell is left as infinity.

Fill each cell with the distance between ith and jth vertex
Now, create a matrix A¹ using matrix A⁰. The elements in the first column and the first row are left as they are. The remaining cells are filled in the following way.

Let k be the intermediate vertex in the shortest path from source to destination. In this step, k is the first vertex. A[i][j] is filled with (A[i][k] + A[k][j]) if (A[i][j] > A[i][k] + A[k][j]).

That is, if the direct distance from the source to the destination is greater than the path through the vertex k, then the cell is filled with A[i][k] + A[k][j].

In this step, k is vertex 1. We calculate the distance from source vertex to destination vertex through this vertex k.

Calculate the distance from the source vertex to destination vertex through this vertex k

For example: For A¹[2, 4], the direct distance from vertex 2 to 4 is 4 and the sum of the distance from vertex 2 to 4 through vertex (ie. from vertex 2 to 1 and from vertex 1 to 4) is 7. Since 4 < 7, A⁰[2, 4] is filled with 4.
Similarly, A² is created using A¹. The elements in the second column and the second row are left as they are.

In this step, k is the second vertex (i.e. vertex 2). The remaining steps are the same as in step 2.

Calculate the distance from the source vertex to destination vertex through this vertex 2
Similarly, A³ and A⁴ is also created.

Calculate the distance from the source vertex to destination vertex through this vertex 3

Calculate the distance from the source vertex to destination vertex through this vertex 4
A⁴ gives the shortest path between each pair of vertices.

Floyd-Warshall Algorithm

n = no of vertices
A = matrix of dimension n*n
for k = 1 to n
    for i = 1 to n
        for j = 1 to n
            A^k[i, j] = min (A^k-1[i, j], A^k-1[i, k] + A^k-1[k, j])
return A

Python, Java and C/C++ Examples

# Floyd Warshall Algorithm in python


# The number of vertices
nV = 4

INF = 999


# Algorithm implementation
def floyd_warshall(G):
    distance = list(map(lambda i: list(map(lambda j: j, i)), G))

    # Adding vertices individually
    for k in range(nV):
        for i in range(nV):
            for j in range(nV):
                distance[i][j] = min(distance[i][j], distance[i][k] + distance[k][j])
    print_solution(distance)


# Printing the solution
def print_solution(distance):
    for i in range(nV):
        for j in range(nV):
            if(distance[i][j] == INF):
                print("INF", end=" ")
            else:
                print(distance[i][j], end="  ")
        print(" ")


G = [[0, 3, INF, 5],
         [2, 0, INF, 4],
         [INF, 1, 0, INF],
         [INF, INF, 2, 0]]
floyd_warshall(G)

// Floyd Warshall Algorithm in Java

class FloydWarshall {
  final static int INF = 9999, nV = 4;

  // Implementing floyd warshall algorithm
  void floydWarshall(int graph[][]) {
    int matrix[][] = new int[nV][nV];
    int i, j, k;

    for (i = 0; i < nV; i++)
      for (j = 0; j < nV; j++)
        matrix[i][j] = graph[i][j];

    // Adding vertices individually
    for (k = 0; k < nV; k++) {
      for (i = 0; i < nV; i++) {
        for (j = 0; j < nV; j++) {
          if (matrix[i][k] + matrix[k][j] < matrix[i][j])
            matrix[i][j] = matrix[i][k] + matrix[k][j];
        }
      }
    }
    printMatrix(matrix);
  }

  void printMatrix(int matrix[][]) {
    for (int i = 0; i < nV; ++i) {
      for (int j = 0; j < nV; ++j) {
        if (matrix[i][j] == INF)
          System.out.print("INF ");
        else
          System.out.print(matrix[i][j] + "  ");
      }
      System.out.println();
    }
  }

  public static void main(String[] args) {
    int graph[][] = { { 0, 3, INF, 5 }, { 2, 0, INF, 4 }, { INF, 1, 0, INF }, { INF, INF, 2, 0 } };
    FloydWarshall a = new FloydWarshall();
    a.floydWarshall(graph);
  }
}

// Floyd-Warshall Algorithm in C

#include <stdio.h>

// defining the number of vertices
#define nV 4

#define INF 999

void printMatrix(int matrix[][nV]);

// Implementing floyd warshall algorithm
void floydWarshall(int graph[][nV]) {
  int matrix[nV][nV], i, j, k;

  for (i = 0; i < nV; i++)
    for (j = 0; j < nV; j++)
      matrix[i][j] = graph[i][j];

  // Adding vertices individually
  for (k = 0; k < nV; k++) {
    for (i = 0; i < nV; i++) {
      for (j = 0; j < nV; j++) {
        if (matrix[i][k] + matrix[k][j] < matrix[i][j])
          matrix[i][j] = matrix[i][k] + matrix[k][j];
      }
    }
  }
  printMatrix(matrix);
}

void printMatrix(int matrix[][nV]) {
  for (int i = 0; i < nV; i++) {
    for (int j = 0; j < nV; j++) {
      if (matrix[i][j] == INF)
        printf("%4s", "INF");
      else
        printf("%4d", matrix[i][j]);
    }
    printf("\n");
  }
}

int main() {
  int graph[nV][nV] = {{0, 3, INF, 5},
             {2, 0, INF, 4},
             {INF, 1, 0, INF},
             {INF, INF, 2, 0}};
  floydWarshall(graph);
}

// Floyd-Warshall Algorithm in C++

#include <iostream>
using namespace std;

// defining the number of vertices
#define nV 4

#define INF 999

void printMatrix(int matrix[][nV]);

// Implementing floyd warshall algorithm
void floydWarshall(int graph[][nV]) {
  int matrix[nV][nV], i, j, k;

  for (i = 0; i < nV; i++)
    for (j = 0; j < nV; j++)
      matrix[i][j] = graph[i][j];

  // Adding vertices individually
  for (k = 0; k < nV; k++) {
    for (i = 0; i < nV; i++) {
      for (j = 0; j < nV; j++) {
        if (matrix[i][k] + matrix[k][j] < matrix[i][j])
          matrix[i][j] = matrix[i][k] + matrix[k][j];
      }
    }
  }
  printMatrix(matrix);
}

void printMatrix(int matrix[][nV]) {
  for (int i = 0; i < nV; i++) {
    for (int j = 0; j < nV; j++) {
      if (matrix[i][j] == INF)
        printf("%4s", "INF");
      else
        printf("%4d", matrix[i][j]);
    }
    printf("\n");
  }
}

int main() {
  int graph[nV][nV] = {{0, 3, INF, 5},
             {2, 0, INF, 4},
             {INF, 1, 0, INF},
             {INF, INF, 2, 0}};
  floydWarshall(graph);
}

Floyd Warshall Algorithm Complexity

Time Complexity

There are three loops. Each loop has constant complexities. So, the time complexity of the Floyd-Warshall algorithm is O(n³).

Space Complexity

The space complexity of the Floyd-Warshall algorithm is O(n²).

Floyd Warshall Algorithm Applications

To find the shortest path is a directed graph
To find the transitive closure of directed graphs
To find the Inversion of real matrices
For testing whether an undirected graph is bipartite

Table of Contents

Definition
How Floyd-Warshall Algorithm Works?
Floyd-Warshall Algorithm
Python, Java and C/C++ Examples
Floyd Warshall Algorithm Complexity
Floyd Warshall Algorithm Applications

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Dynamic Programming

Longest Common Sequence