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We have already seen about breadth first search in level order traversal of binary tree.
Table of Contents
Graph traversal Algorithms:
Breadth first search is graph traversal algorithm. In this algorithm, lets say we start with node i, then we will visit neighbours of i, then neighbours of neighbours of i and so on.
It is very much similar to which is used in binary tree. We use queue to traverse graph. We put first node in queue . It repeatedly extracts node and put its neighbours in the queue. Only difference with respect to binary tree is that we need to track if node have been visited before or not. It can be easily done with help of boolean variable visited in the node. If node have been already visited then we won’t visit it again.
Algorithm:
Steps for Breadth first search:
- Create empty queue and push root node to it.
- Do the following when queue is not empty
- Pop a node from queue and print it.
- Find neighbours of node with the help of adjacency matrix and check if node is already visited or not.
- Push neighbours of node into queue if not null
Lets understand with the help of example:
Lets say graph is:
Java BFS Example
There are two ways to represent a graph.
- Using Neighbours list
- Using Adjacency Matrix
Using Neighbours list
In this, you can have List<Node> as neighbours in Node class as below.
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package org.arpit.java2blog.graph; import java.util.ArrayList; import java.util.LinkedList; import java.util.List; import java.util.Queue; public class BreadthFirstSearchExampleNeighbourList { private Queue<Node> queue; static ArrayList<Node> nodes=new ArrayList<Node>(); static class Node { int data; boolean visited; List<Node> neighbours; Node(int data) { this.data=data; this.neighbours=new ArrayList<>(); } public void addneighbours(Node neighbourNode) { this.neighbours.add(neighbourNode); } public List<Node> getNeighbours() { return neighbours; } public void setNeighbours(List<Node> neighbours) { this.neighbours = neighbours; } } public BreadthFirstSearchExampleNeighbourList() { queue = new LinkedList<Node>(); } public void bfs(Node node) { queue.add(node); node.visited=true; while (!queue.isEmpty()) { Node element=queue.remove(); System.out.print(element.data + "t"); List<Node> neighbours=element.getNeighbours(); for (int i = 0; i < neighbours.size(); i++) { Node n=neighbours.get(i); if(n!=null && !n.visited) { queue.add(n); n.visited=true; } } } } public static void main(String arg[]) { Node node40 =new Node(40); Node node10 =new Node(10); Node node20 =new Node(20); Node node30 =new Node(30); Node node60 =new Node(60); Node node50 =new Node(50); Node node70 =new Node(70); node40.addneighbours(node10); node40.addneighbours(node20); node10.addneighbours(node30); node20.addneighbours(node10); node20.addneighbours(node30); node20.addneighbours(node60); node20.addneighbours(node50); node30.addneighbours(node60); node60.addneighbours(node70); node50.addneighbours(node70); System.out.println("The BFS traversal of the graph is "); BreadthFirstSearchExampleNeighbourList bfsExample = new BreadthFirstSearchExampleNeighbourList(); bfsExample.bfs(node40); } } |
When you run above program, you will get below output:
The BFS traversal of the graph is
40 10 20 30 60 50 70
40 10 20 30 60 50 70
Using Adjacency Matrix
Adjacency_matrix is used to find the connection between two nodes.
if adjacency_matrix[i][j]==1, then nodes at index i and index j are connected
Below diagram will help you to understand adjacency matrix.
Create BreadthFirstSearchExample.java
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package org.arpit.java2blog.graph; import java.util.ArrayList; import java.util.LinkedList; import java.util.Queue; public class BreadthFirstSearchExample { private Queue<Node> queue; static ArrayList<Node> nodes=new ArrayList<Node>(); static class Node { int data; boolean visited; Node(int data) { this.data=data; } } public BreadthFirstSearchExample() { queue = new LinkedList<Node>(); } // find neighbors of node using adjacency matrix // if adjacency_matrix[i][j]==1, then nodes at index i and index j are connected public ArrayList<Node> findNeighbours(int adjacency_matrix[][],Node x) { int nodeIndex=-1; ArrayList<Node> neighbours=new ArrayList<Node>(); for (int i = 0; i < nodes.size(); i++) { if(nodes.get(i).equals(x)) { nodeIndex=i; break; } } if(nodeIndex!=-1) { for (int j = 0; j < adjacency_matrix[nodeIndex].length; j++) { if(adjacency_matrix[nodeIndex][j]==1) { neighbours.add(nodes.get(j)); } } } return neighbours; } public void bfs(int adjacency_matrix[][], Node node) { queue.add(node); node.visited=true; while (!queue.isEmpty()) { Node element=queue.remove(); System.out.print(element.data + "t"); ArrayList<Node> neighbours=findNeighbours(adjacency_matrix,element); for (int i = 0; i < neighbours.size(); i++) { Node n=neighbours.get(i); if(n!=null && !n.visited) { queue.add(n); n.visited=true; } } } } public static void main(String arg[]) { Node node40 =new Node(40); Node node10 =new Node(10); Node node20 =new Node(20); Node node30 =new Node(30); Node node60 =new Node(60); Node node50 =new Node(50); Node node70 =new Node(70); nodes.add(node40); nodes.add(node10); nodes.add(node20); nodes.add(node30); nodes.add(node60); nodes.add(node50); nodes.add(node70); int adjacency_matrix[][] = { {0,1,1,0,0,0,0}, // Node 1: 40 {0,0,0,1,0,0,0}, // Node 2 :10 {0,1,0,1,1,1,0}, // Node 3: 20 {0,0,0,0,1,0,0}, // Node 4: 30 {0,0,0,0,0,0,1}, // Node 5: 60 {0,0,0,0,0,0,1}, // Node 6: 50 {0,0,0,0,0,0,0}, // Node 7: 70 }; System.out.println("The BFS traversal of the graph is "); BreadthFirstSearchExample bfsExample = new BreadthFirstSearchExample(); bfsExample.bfs(adjacency_matrix, node40); } } |
When you run above program, you will get below output:
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1 2 3 4 |
The BFS traversal of the graph is 40 10 20 30 60 50 70 |
Please go through Algorithm Interview Programs in java  for more such programs.
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