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disjointPaths.cpp
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disjointPaths.cpp
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// C++ program for implementation of Ford Fulkerson algorithm
#include <iostream>
#include <limits.h>//INT_MAX
#include <string.h>
#include <queue>//coz, using BFS
using namespace std;
// Number of vertices in given graph
#define n 3
#define V 2*n+2
/* Returns true if there is a path from source 's' to sink 't' in
residual graph. Also fills parent[] to store the path */
bool bfs(int rGraph[V][V], int s, int t, int parent[])
{
// Create a visited array and mark all vertices as not visited
bool visited[V];
memset(visited, 0, sizeof(visited));//initialise the array with zeros //needs string.h
// Create a queue, enqueue source vertex and mark source vertex as visited
queue <int> q;
q.push(s);
visited[s] = true;
parent[s] = -1;
// Standard BFS Loop
while (!q.empty())
{
int u = q.front();
q.pop();
for (int v=0; v<V; v++)
{
if (visited[v]==false && rGraph[u][v] > 0)
{
q.push(v);
parent[v] = u;
visited[v] = true;
}
}
}
// If we reached sink in BFS starting from source, then return true, else false
return (visited[t] == true);
}
// Returns the maximum flow from s to t in the given graph
int fordFulkerson(int graph[V][V], int s, int t)
{
int u, v;
// Create a residual graph and fill the residual graph with
// given capacities in the original graph as residual capacities in residual graph
int rGraph[V][V]; // Residual graph where rGraph[i][j] indicates
// residual capacity of edge from i to j (if there
// is an edge. If rGraph[i][j] is 0, then there is not)
for (u = 0; u < V; u++)
for (v = 0; v < V; v++)
rGraph[u][v] = graph[u][v];
int parent[V]; // This array is filled by BFS and to store path to retrace the patth
int max_flow = 0; // There is no flow initially
// Augment the flow while tere is path from source to sink
while (bfs(rGraph, s, t, parent))
{
// Find minimum residual capacity of the edges along the
// path filled by BFS. Or we can say find the maximum flow
// through the path found.
int path_flow = INT_MAX;
for (v=t; v!=s; v=parent[v])
{
u = parent[v];
path_flow = min(path_flow, rGraph[u][v]);
}//now the path_flow is the min capacity of the path
// update residual capacities of the edges and reverse edges along the path
for (v=t; v != s; v=parent[v])
{
u = parent[v];
rGraph[u][v] -= path_flow;
rGraph[v][u] += path_flow;
}
// Add path flow to overall flow
max_flow += path_flow;
}
// Return the overall flow
return max_flow;
}
// Driver program to test above functions
int main()
{
// Let us create a graph shown in the above example
//G is initial graph
// 1` 2` 3`
int G[n][n]={ {1, 0, 0},
{1, 0, 0},
{0, 1, 0}
};
int graph[V][V];//has sink and terminal
int i=0,j=0;
for(i=0;i<V;i++)//zero matrix
{
for(j=0;j<V;j++)
{
graph[i][j]=0;
}
}
i=0;//source to n nodes
for(j=1;j<n+1;j++)
{
graph[i][j]=1;
}
j=2*n+1;//n nodes to terminal
for(i=n+1;i<2*n+1;i++)
{
graph[i][j]=1;
}
//copy G to graph
for(i=1;i<n+1;i++)
{
for(j=n+1;j<2*n+1;j++)
{
graph[i][j]=G[i-1][j-n-1];
}
}
// // s 1 2 3 1` 2` 3` t
// int graph[V][V] = { {0, 1, 1, 1, 0, 0, 0, 0},
// {0, 0, 0, 0, 1, 0, 0, 0},
// {0, 0, 0, 0, 1, 0, 0, 0},// 1 - 1`
// {0, 0, 0, 0, 0, 1 ,0, 0},// s/-\ 2 / 2`/-\t
// {0, 0, 0, 0, 0, 0, 0, 1},// 3 / 3`
// {0, 0, 0, 0, 0, 0, 0, 1},
// {0, 0, 0, 0, 0, 0, 0, 1},
// {0, 0, 0, 0, 0, 0, 0, 0}
// };
// cout << "The maximum possible flow is " << fordFulkerson(graph, 0, 5);
cout << "The number of disjoint paths : " << fordFulkerson(graph, 0, V-1);
return 0;
}