### nk

A Computer Science portal for geeks. It contains well written, well thought and well explained computer science and programming articles, quizzes and practice/competitive programming/company interview Questions. Problem: Given an unweighted undirected graph, we have to find the shortest path from the given source to the given destination using the Breadth-First Search algorithm. The idea is to traverse the graph using Breadth-First Search Traversal until we reach the end node and print the route by tracing back the path to the start node. With Dijkstra's Algorithm, you can find the shortest **path** between nodes in a graph. Particularly, you can find the shortest **path** from a node (called the "**source** node") to **all** other nodes in the graph, producing a shortest-**path** tree. This algorithm is used in GPS devices to find the shortest **path** between the current location and the **destination**. Also provide the algorithm to **print** the **paths** for a **source** vertex and a **destination** vertex. For the pseudocode consider the following definition of the graph - **Given** a weighted directed graph, G = (V, E) with a weight function wthat maps edges to real-valued weights. w(u, v) denotes the weight of an edge (u, v). 1. You are **given** **a** graph, a **source** vertex and a **destination** vertex. 2. You are required to find and **print** **all** **paths** between **source** and **destination**. **Print** them in lexicographical order. E.g. Check the following **paths** 012546 01256 032546 03256 The lexicographically smaller **path** is printed first. Input Format Input has been managed for you Output. Solving rat in maze **using** DFS. truckboy98. Hello, I am trying to represent a maze **using** two classes: Maze and Cell. A Maze object is a rectangular grid of cells i.e., a 2. A Maze is **given** **as** N*N binary matrix of blocks where **source** block is the upper left most block i.e., maze [0] [0] and **destination** block is lower rightmost block i.e., maze [N-1. A Destination-Oriented Directed Acyclic Graph (DODAG) is a term used in [ 1] to describe a directed acyclic graph with exactly one root, where a root is a node which has no outgoing edges. Diverse multipath routing algorithms make use of DODAGs, such as [ 2 – 8 ]. Use two arrays, say dist [] to store the shortest distance from the **source** vertex and **paths** [] of size N, to store the number of. Graph - Count **all paths** between **source** and **destination**. April 5,. **Source** = K **destination** = P Output K -> T -> Y -> A -> P K -> T -> Y -> P K -> A -> P Here, we have found **paths** **from** K to P. We have traversed **paths** and printed **all** **paths** **from** K that direct us to P. To **print** **all** **paths** **from** **source** **to** **destination**, we will have to traverse the graph and store **paths** and then **print** valid **paths**. **BFS** for a graph is similar to a tree, the only difference being graphs might contain cycles. Unlike depth-**first search**, **all** of the neighbor nodes at a certain depth are explored before moving on to the next level. **BFS** Algorithm. The general process of exploring a graph **using** breadth-**first search** includes the following steps:-. **Source** = K **destination** = P Output K -> T -> Y -> A -> P K -> T -> Y -> P K -> A -> P Here, we have found **paths** **from** K to P. We have traversed **paths** and printed **all** **paths** **from** K that direct us to P. To **print** **all** **paths** **from** **source** **to** **destination**, we will have to traverse the graph and store **paths** and then **print** valid **paths**. Calculates **all** the simple **paths from a given** node to some other nodes (or **all** of them) in a graph. A **path** is simple if its vertices are unique, i.e. no vertex is visited more than once. Note that potentially there are exponentially many **paths** between two vertices of a graph, especially if your graph is lattice-like. **print** **path** between two nodes in a graph **using** **bfs**. B) Mark the current node as visited and enqueue it and it will be used to get **all** adjacent vertices of a vertex C) Dequeue a vertex from queue and **print** . The root of the tree is the node you started the breadth-first search **from**. This path can be split into two parts: P 1 which consists of only marked nodes (at least the starting vertex s is part of P 1 ), and the rest of the path P 2 (it may include a marked vertex, but it always starts with an unmarked vertex). Let's denote the first vertex of the path P 2 as p, and the last vertex of the path P 1 as q. The steps involved in the **BFS** algorithm to explore a graph are **given** as follows -. Step 1: SET STATUS = 1 (ready state) for each node in G. Step 2: Enqueue the starting node A and set its STATUS = 2 (waiting state) Step 3: Repeat Steps 4 and 5 until QUEUE is empty. Step 4: Dequeue a node N. Process it and set its STATUS = 3 (processed state). Java program for **Print** **all** the **paths** **from** the **source** **to** **destination** in directed graph. Here problem description and explanation. /* Java program for **Print** **all** **path** between **given** vertices in a directed graph */ class AjlistNode { // Vertices node key public int id; public AjlistNode next; public AjlistNode (int id) { // Set value of node key. Code: C++. 2021-04-22 01:12:38. // CPP code for printing shortest **path** between // two vertices of unweighted graph #include <bits/stdc++.h> **using** namespace std; // utility function to form edge between two vertices // **source** and dest void add_edge(vector<int> adj [], int src, int dest) { adj [src].push_back (dest); adj [dest].push_back (src. Problem: Given an unweighted undirected graph, we have to find the shortest path from the given source to the given destination using the Breadth-First Search algorithm. The idea is to traverse the graph using Breadth-First Search Traversal until we reach the end node and print the route by tracing back the path to the start node. Approach: The idea is to use a queue and apply **bfs** and use a variable count to store the number of possible **paths**. Make a pair of row and column and insert (0, 0) into the queue. Kotlin program for **Print** **all** the **paths** **from** the **source** **to** **destination** in directed graph. Here problem description and other solutions. /* Kotlin program for **Print** **all** **path** between **given** vertices in a directed graph */ class AjlistNode { // Vertices node key var id: Int; var next: AjlistNode ? ; constructor (id: Int) { // Set value of node key. Objective: **Given** **a** graph and a **source** vertex write an algorithm to find the shortest **path** **from** the **source** vertex to **all** the vertices and **print** the **paths** **all** well. We strongly recommend reading the following before continuing to read Graph Representation - Adjacency List Dijkstra's shortest **path** > algorithm - Priority Queue method We will use the same approach with some extra steps to.