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Bellman–Ford Algorithm.cpp
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Bellman–Ford Algorithm.cpp
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// BELLMAN–FORD ALGORITHM
// OVERVIEW OF THE ALGORITHM :
// Given a graph and a source vertex src in graph, find shortest paths from src to all vertices in the given graph.
// The graph may contain negative weight edges.
// We have discussed Dijkstra’s algorithm for this problem.
// Dijkstra’s algorithm is a Greedy algorithm and time complexity is O(VLogV) (with the use of Fibonacci heap).
// Dijkstra doesn’t work for Graphs with negative weight edges, Bellman-Ford works for such graphs.
// Bellman-Ford is also simpler than Dijkstra and suites well for distributed systems.
// But time complexity of Bellman-Ford is O(VE), which is more than Dijkstra's algorithm.
// Algorithm
// Following are the detailed steps.
// Input: Graph and a source vertex src
// Output: Shortest distance to all vertices from src. If there is a negative weight cycle,
// then shortest distances are not calculated, negative weight cycle is reported.
// 1) This step initializes distances from the source to all vertices as infinite and distance to the source itself as 0.
// Create an array dist[] of size |V| with all values as infinite except dist[src] where src is source vertex.
// 2) This step calculates shortest distances. Do following |V|-1 times where |V| is the number of vertices in given graph.
// …..a) Do following for each edge u-v
// ………………If dist[v] > dist[u] + weight of edge uv, then update dist[v]
// ………………….dist[v] = dist[u] + weight of edge uv
// 3) This step reports if there is a negative weight cycle in graph. Do following for each edge u-v
// ……If dist[v] > dist[u] + weight of edge uv, then “Graph contains negative weight cycle”
// The idea of step 3 is, step 2 guarantees the shortest distances if the graph doesn’t contain a negative weight cycle.
// If we iterate through all edges one more time and get a shorter path for any vertex,
// then there is a negative weight cycle
// IMPLEMENTATION OF DIJKSTRA'S ALGORITHM IN C++ :
// A C++ program for Bellman-Ford's single source
// shortest path algorithm.
#include <bits/stdc++.h>
#include <stdio.h>
#include <stdlib.h>
using namespace std;
// a structure to represent a weighted edge in graph
struct Edge {
int src, dest, weight;
};
// a structure to represent a connected, directed and
// weighted graph
struct Graph {
// V-> Number of vertices, E-> Number of edges
int V, E;
// graph is represented as an array of edges.
struct Edge* edge;
};
// Creates a graph with V vertices and E edges
struct Graph* createGraph(int V, int E)
{
struct Graph* graph = new Graph;
graph->V = V;
graph->E = E;
graph->edge = new Edge[E];
return graph;
}
// A utility function used to print the solution
void printArr(int dist[], int n)
{
printf("Vertex Distance from Source\n");
for (int i = 0; i < n; ++i)
printf("%d \t\t %d\n", i, dist[i]);
}
// The main function that finds shortest distances from src to
// all other vertices using Bellman-Ford algorithm. The function
// also detects negative weight cycle
void BellmanFord(struct Graph* graph, int src)
{
int V = graph->V;
int E = graph->E;
int dist[V];
// Step 1: Initialize distances from src to all other vertices
// as INFINITE
for (int i = 0; i < V; i++)
dist[i] = INT_MAX;
dist[src] = 0;
// Step 2: Relax all edges |V| - 1 times. A simple shortest
// path from src to any other vertex can have at-most |V| - 1
// edges
for (int i = 1; i <= V - 1; i++) {
for (int j = 0; j < E; j++) {
int u = graph->edge[j].src;
int v = graph->edge[j].dest;
int weight = graph->edge[j].weight;
if (dist[u] != INT_MAX && dist[u] + weight < dist[v])
dist[v] = dist[u] + weight;
}
}
// Step 3: check for negative-weight cycles. The above step
// guarantees shortest distances if graph doesn't contain
// negative weight cycle. If we get a shorter path, then there
// is a cycle.
for (int i = 0; i < E; i++) {
int u = graph->edge[i].src;
int v = graph->edge[i].dest;
int weight = graph->edge[i].weight;
if (dist[u] != INT_MAX && dist[u] + weight < dist[v]) {
printf("Graph contains negative weight cycle");
return; // If negative cycle is detected, simply return
}
}
printArr(dist, V);
return;
}
// Driver program to test above functions
int main()
{
/* Let us create the graph given in above example */
int V = 5; // Number of vertices in graph
int E = 8; // Number of edges in graph
struct Graph* graph = createGraph(V, E);
// add edge 0-1 (or A-B in above figure)
graph->edge[0].src = 0;
graph->edge[0].dest = 1;
graph->edge[0].weight = -1;
// add edge 0-2 (or A-C in above figure)
graph->edge[1].src = 0;
graph->edge[1].dest = 2;
graph->edge[1].weight = 4;
// add edge 1-2 (or B-C in above figure)
graph->edge[2].src = 1;
graph->edge[2].dest = 2;
graph->edge[2].weight = 3;
// add edge 1-3 (or B-D in above figure)
graph->edge[3].src = 1;
graph->edge[3].dest = 3;
graph->edge[3].weight = 2;
// add edge 1-4 (or A-E in above figure)
graph->edge[4].src = 1;
graph->edge[4].dest = 4;
graph->edge[4].weight = 2;
// add edge 3-2 (or D-C in above figure)
graph->edge[5].src = 3;
graph->edge[5].dest = 2;
graph->edge[5].weight = 5;
// add edge 3-1 (or D-B in above figure)
graph->edge[6].src = 3;
graph->edge[6].dest = 1;
graph->edge[6].weight = 1;
// add edge 4-3 (or E-D in above figure)
graph->edge[7].src = 4;
graph->edge[7].dest = 3;
graph->edge[7].weight = -3;
BellmanFord(graph, 0);
}