309 lines
12 KiB
Java
309 lines
12 KiB
Java
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/*This Java program is to Implement Johnson’s algorithm. Johnson’s algorithm is a way to find the shortest paths between all pairs of vertices in a sparse, edge weighted, directed graph. It allows some of the edge weights to be negative numbers, but no negative-weight cycles may exist. It works by using the Bellman–Ford algorithm to compute a transformation of the input graph that removes all negative weights, allowing Dijkstra’s algorithm to be used on the transformed graph.*/
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import java.util.InputMismatchException;
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import java.util.Scanner;
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public class JohnsonsAlgorithm
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{
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private int SOURCE_NODE;
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private int numberOfNodes;
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private int augmentedMatrix[][];
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private int potential[];
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private BellmanFord bellmanFord;
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private DijkstraShortesPath dijsktraShortesPath;
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private int[][] allPairShortestPath;
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public static final int MAX_VALUE = 999;
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public JohnsonsAlgorithm(int numberOfNodes)
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{
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this.numberOfNodes = numberOfNodes;
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augmentedMatrix = new int[numberOfNodes + 2][numberOfNodes + 2];
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SOURCE_NODE = numberOfNodes + 1;
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potential = new int[numberOfNodes + 2];
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bellmanFord = new BellmanFord(numberOfNodes + 1);
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dijsktraShortesPath = new DijkstraShortesPath(numberOfNodes);
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allPairShortestPath = new int[numberOfNodes + 1][numberOfNodes + 1];
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}
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public void johnsonsAlgorithms(int adjacencyMatrix[][])
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{
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computeAugmentedGraph(adjacencyMatrix);
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bellmanFord.BellmanFordEvaluation(SOURCE_NODE, augmentedMatrix);
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potential = bellmanFord.getDistances();
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int reweightedGraph[][] = reweightGraph(adjacencyMatrix);
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for (int i = 1; i <= numberOfNodes; i++)
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{
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for (int j = 1; j <= numberOfNodes; j++)
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{
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System.out.print(reweightedGraph[i][j] + "\t");
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}
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System.out.println();
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}
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for (int source = 1; source <= numberOfNodes; source++)
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{
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dijsktraShortesPath.dijkstraShortestPath(source, reweightedGraph);
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int[] result = dijsktraShortesPath.getDistances();
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for (int destination = 1; destination <= numberOfNodes; destination++)
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{
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allPairShortestPath[source][destination] = result[destination]
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+ potential[destination] - potential[source];
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}
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}
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System.out.println();
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for (int i = 1; i<= numberOfNodes; i++)
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{
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System.out.print("\t"+i);
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}
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System.out.println();
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for (int source = 1; source <= numberOfNodes; source++)
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{
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System.out.print( source +"\t" );
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for (int destination = 1; destination <= numberOfNodes; destination++)
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{
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System.out.print(allPairShortestPath[source][destination]+ "\t");
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}
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System.out.println();
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}
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}
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private void computeAugmentedGraph(int adjacencyMatrix[][])
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{
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for (int source = 1; source <= numberOfNodes; source++)
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{
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for (int destination = 1; destination <= numberOfNodes; destination++)
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{
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augmentedMatrix[source][destination] = adjacencyMatrix[source][destination];
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}
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}
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for (int destination = 1; destination <= numberOfNodes; destination++)
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{
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augmentedMatrix[SOURCE_NODE][destination] = 0;
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}
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}
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private int[][] reweightGraph(int adjacencyMatrix[][])
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{
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int[][] result = new int[numberOfNodes + 1][numberOfNodes + 1];
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for (int source = 1; source <= numberOfNodes; source++)
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{
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for (int destination = 1; destination <= numberOfNodes; destination++)
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{
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result[source][destination] = adjacencyMatrix[source][destination]
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+ potential[source] - potential[destination];
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}
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}
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return result;
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}
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public static void main(String... arg)
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{
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int adjacency_matrix[][];
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int number_of_vertices;
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Scanner scan = new Scanner(System.in);
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try
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{
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System.out.println("Enter the number of vertices");
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number_of_vertices = scan.nextInt();
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adjacency_matrix = new int[number_of_vertices + 1][number_of_vertices + 1];
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System.out.println("Enter the Weighted Matrix for the graph");
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for (int i = 1; i <= number_of_vertices; i++)
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{
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for (int j = 1; j <= number_of_vertices; j++)
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{
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adjacency_matrix[i][j] = scan.nextInt();
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if (i == j)
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{
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adjacency_matrix[i][j] = 0;
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continue;
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}
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if (adjacency_matrix[i][j] == 0)
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{
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adjacency_matrix[i][j] = MAX_VALUE;
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}
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}
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}
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JohnsonsAlgorithm johnsonsAlgorithm = new JohnsonsAlgorithm(number_of_vertices);
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johnsonsAlgorithm.johnsonsAlgorithms(adjacency_matrix);
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}
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catch (InputMismatchException inputMismatch)
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{
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System.out.println("Wrong Input Format");
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}
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scan.close();
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}
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}
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class BellmanFord
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{
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private int distances[];
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private int numberofvertices;
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public static final int MAX_VALUE = 999;
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public BellmanFord(int numberofvertices)
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{
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this.numberofvertices = numberofvertices;
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distances = new int[numberofvertices + 1];
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}
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public void BellmanFordEvaluation(int source, int adjacencymatrix[][])
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{
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for (int node = 1; node <= numberofvertices; node++)
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{
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distances[node] = MAX_VALUE;
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}
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distances[source] = 0;
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for (int node = 1; node <= numberofvertices - 1; node++)
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{
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for (int sourcenode = 1; sourcenode <= numberofvertices; sourcenode++)
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{
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for (int destinationnode = 1; destinationnode <= numberofvertices; destinationnode++)
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{
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if (adjacencymatrix[sourcenode][destinationnode] != MAX_VALUE)
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{
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if (distances[destinationnode] > distances[sourcenode]
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+ adjacencymatrix[sourcenode][destinationnode])
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{
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distances[destinationnode] = distances[sourcenode]
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+ adjacencymatrix[sourcenode][destinationnode];
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}
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}
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}
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}
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}
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for (int sourcenode = 1; sourcenode <= numberofvertices; sourcenode++)
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{
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for (int destinationnode = 1; destinationnode <= numberofvertices; destinationnode++)
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{
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if (adjacencymatrix[sourcenode][destinationnode] != MAX_VALUE)
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{
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if (distances[destinationnode] > distances[sourcenode]
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+ adjacencymatrix[sourcenode][destinationnode])
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System.out.println("The Graph contains negative egde cycle");
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}
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}
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}
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}
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public int[] getDistances()
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{
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return distances;
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}
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}
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class DijkstraShortesPath
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{
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private boolean settled[];
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private boolean unsettled[];
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private int distances[];
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private int adjacencymatrix[][];
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private int numberofvertices;
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public static final int MAX_VALUE = 999;
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public DijkstraShortesPath(int numberofvertices)
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{
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this.numberofvertices = numberofvertices;
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}
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public void dijkstraShortestPath(int source, int adjacencymatrix[][])
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{
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this.settled = new boolean[numberofvertices + 1];
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this.unsettled = new boolean[numberofvertices + 1];
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this.distances = new int[numberofvertices + 1];
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this.adjacencymatrix = new int[numberofvertices + 1][numberofvertices + 1];
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int evaluationnode;
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for (int vertex = 1; vertex <= numberofvertices; vertex++)
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{
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distances[vertex] = MAX_VALUE;
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}
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for (int sourcevertex = 1; sourcevertex <= numberofvertices; sourcevertex++)
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{
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for (int destinationvertex = 1; destinationvertex <= numberofvertices; destinationvertex++)
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{
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this.adjacencymatrix[sourcevertex][destinationvertex]
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= adjacencymatrix[sourcevertex][destinationvertex];
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}
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}
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unsettled[source] = true;
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distances[source] = 0;
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while (getUnsettledCount(unsettled) != 0)
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{
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evaluationnode = getNodeWithMinimumDistanceFromUnsettled(unsettled);
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unsettled[evaluationnode] = false;
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settled[evaluationnode] = true;
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evaluateNeighbours(evaluationnode);
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}
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}
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public int getUnsettledCount(boolean unsettled[])
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{
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int count = 0;
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for (int vertex = 1; vertex <= numberofvertices; vertex++)
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{
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if (unsettled[vertex] == true)
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{
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count++;
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}
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}
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return count;
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}
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public int getNodeWithMinimumDistanceFromUnsettled(boolean unsettled[])
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{
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int min = MAX_VALUE;
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int node = 0;
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for (int vertex = 1; vertex <= numberofvertices; vertex++)
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{
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if (unsettled[vertex] == true && distances[vertex] < min)
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{
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node = vertex;
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min = distances[vertex];
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}
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}
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return node;
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}
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public void evaluateNeighbours(int evaluationNode)
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{
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int edgeDistance = -1;
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int newDistance = -1;
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for (int destinationNode = 1; destinationNode <= numberofvertices; destinationNode++)
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{
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if (settled[destinationNode] == false)
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{
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if (adjacencymatrix[evaluationNode][destinationNode] != MAX_VALUE)
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{
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edgeDistance = adjacencymatrix[evaluationNode][destinationNode];
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newDistance = distances[evaluationNode] + edgeDistance;
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if (newDistance < distances[destinationNode])
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{
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distances[destinationNode] = newDistance;
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}
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unsettled[destinationNode] = true;
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}
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}
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}
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}
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public int[] getDistances()
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{
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return distances;
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}
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}
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/*
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Enter the number of vertices
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4
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Enter the Weighted Matrix for the graph
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0 0 3 0
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2 0 0 0
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0 7 0 1
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6 0 0 0
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All pair shortest path is
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1 2 3 4
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1 0 10 3 4
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2 2 0 5 6
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3 7 7 0 1
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4 6 16 9 0
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