Given two nodes, source and destination, count the number of ways or paths between these two vertices in the directed graph. 3 elements arranged at positions 1, 7 and 12, resulting in a minimum distance of 5 (between 7 and 12) A Naive Solution is to consider all subsets of size 3 and find the minimum distance for every subset. Following figure is taken from this source. Any such node should be counted only once. So the space needed is O(V). Every item of set is a pair. You are given heights, a 2D array of size rows x columns, where heights[row][col] represents the height of cell (row, col). A Bellman-Ford algorithm is also guaranteed to find the shortest path in a graph, similar to. Output: 2. Lesser overheads than Bellman-Ford. Below is the step by step algorithm to solve this problem:Queries to check if the path between two nodes in a tree is a palindrome. Perform DFS at Root. The idea is to use Dijkstra’s algorithm to find the shortest path from source vertex a to all other vertices in the graph using the straight edges and store the result in array da[], and then from the destination vertex b to all other vertices and store the result in db[]. Given a graph of N Nodes and E edges in form of {U, V, W} such that there exists an edge between U and V with weight W. The main idea is to recursively get the longest path from the left. Given an unweighted graph, a source, and a destination, we need to find the shortest path from source to destination in the graph in the most optimal way. Given a directed acyclic graph (DAG) with n nodes labeled from 0 to n-1. Note: edges [i] is defined as u, v and weight. Given a boolean matrix of size RxC where each cell contains either 0 or 1, modify it such that if a matrix cell matrix [i] [j] is 1 then all the cells in its ith row and jth column will become 1. You are. It uses the Bellman-Ford algorithm to re-weight the original graph, removing all negative weights. You can also go from S=1 to T=8 via (1, 2, 5, 8) or (1, 4, 6, 7, 8) but these paths are not shortest. It's based on the observation that edge for which dist + edge_weight is minimum is on the path (when looking backwards). Print root to leaf paths without using recursion. The following steps can be followed to compute the result: If the source is equal to the destination then return 0. You don't need to read input or print anything. Input: source vertex = 0 and destination vertex is = 7. 89% Submissions: 109K+ Points: 4. Below are steps. If the destination is reached, print the vector as one of the possible paths. Keep the following conditions in mYour task is to complete the function printGraph () which takes the integer V denoting the number of vertices and edges as input parameters and returns the list of list denoting the adjacency list. Approach: The main idea here is to use a matrix (2D array) that will keep track of the next node to point if the shortest path changes for any pair of nodes. BFS will be okay. (The values are returned as vector in cpp, as. Given a Directed Graph having V nodes numbered from 0 to V-1, and E directed edges. The task is to find the minimum sum of a falling path through A. For example, a more complex version. In this article, an even optimized recursive approach will be discussed. Note: If the Graph contains a nLength of longest possible route is 24. Follow the steps below to solve the problem: Create dp [N] [N] and ANS [N] [N] tables with all values set to INT_MAX and INT_MIN. When we find “. ; While pq is not empty: . 2) In weighted graph, minimum total weight of edges to duplicate so that given graph converts to a graph with Eulerian Cycle. Given a weighted, directed and connected graph of V vertices and E edges, Find the shortest distance of all the vertex's from the source vertex S. Input: 1 / 2 3 Output: 1 2 #1 3 # Explanation: All possible paths: 1->2 1->3. org. Example 2: Input: K = 3 3 / 2 1 / 5 3 Output: 5 3. Arrays; public class GA { /** * @param args the command line arguments */ public static void main (String [] args) { //computation time long start = System. Here we not only find the shortest distance but also the path. Please to report an issue. Auxiliary Space: O(ALPHABET_SIZE^L+n*L) Approach 2: Using Dynamic Programming. It was conceived by Dutch computer scientist Edsger W. Step 2: Iterate from the end of string. Note: If the Graph contains. Output: 7 3 1 4. Top-down approach for printing Longest Common Subsequence: Follow the steps below for the implementation: Check if one of the two strings is of size zero, then we return an empty string because the LCS, in this case, is empty (base case). Check our Website: case you are thinking to buy courses, please check below: Link to get 20% additional Discount at Coding Ni. Longest path is from 5 to 7 of length 5. Find shortest possible path to type all characters of given string using the remote. Example 1: Input: c = 1, d = 2 Output: 1. Set value of count [i] [0] equal to 1 for 0 <= i < M as the answer of subproblem with a single column is equal to 1. For every vertex being processed, we update distances of its adjacent using distance of current vertex. countSub (n) = 2*Count (n-1) - Repetition. You are given two four digit prime numbers Num1 and Num2. The graph is represented as an adjacency. Given a directed graph where every edge has weight as either 1 or 2, find the shortest path from a given source vertex ‘s’ to a given destination vertex ‘t’. Note: If the Graph contains. The task is to find and print the path between the two given nodes in the binary tree. Output -1 if no monotonic path is possible. A value of cell 2 means Destination. Disclaimer: Please watch Part-1 and Part-2 Part-1:. Bellman-Ford Algorithm: It works for all types of graphs given that negative cycles does not exist in that graph. North, East, West and South where n is value of the cell , We can move to mat [i+n] [j], mat [i-n] [j], mat [i] [j+n], and mat [i] [j-n. e. Improve this answer. The task is to find the sum of weights of the edges of the Minimum Spanning Tree. Nodes should be printed from left to right. Floyd’s cycle finding algorithm or Hare-Tortoise algorithm is a pointer algorithm that uses only two pointers, moving through the sequence at different speeds. Here is a Java example of a shortest path genetic algorithm. Let dp [X] [J] be the shortest path from. add the substring to the list. Given a weighted, undirected and connected graph of V vertices and E edges. Let us consider another. Length of shortest safe route is 13. Approach: For every vertex, we check if it is possible to get the shortest cycle involving this vertex. Num1 and Num2 are prime numbers. Time Complexity: O(N 2) Efficient Approach: The idea is to use Recursion to solve this problem efficiently. Find out the minimum steps a Knight will take to reach the target position. Assume any vertex (let’s say ‘0’) as source and assign dist = 0. The following code prints the shortest distance from the source_node to all the other nodes in the graph. You will need to use the property of the topological. The graph is represented as an adjacency matrix of. Back to Explore Page. The task is to find the minimum number. Note: The Graph doesn't contain any negative weight cycle. Practice. Given adjacency list adj as input parameters . You are given an array graph where graph [i] is a list of. Dijkstra in 1956. Explanation: Starting from the source node 1, the graph contains cycle as 1 -> 2 -> 3 -> 1. The basic idea behind the iterative DFS approach to finding the maximum path sum in a binary tree is to traverse the tree using a stack, maintaining the state of each node as we visit it. Bellman-Ford is a single source shortest path algorithm that determines the shortest path between a given source vertex and every other vertex in a graph. Dijkstra’s algorithm is very similar to Prim’s algorithm for minimum spanning tree. Pop the top-most element from pq. Share. A Graph is a non-linear data structure consisting of vertices and edges. of pq is a pair (weight, vertex). We would like to show you a description here but the site won’t allow us. Auxiliary Space: O (V) 5. Output : 3. In the above algorithm, we start by setting the shortest path distance to the target vertex t as 0 and all other vertices as infinity. Read. Your Task: You don't have to take input. Your task is to complete the function minimumStep() which takes an integer n as inputs and returns the minimum number of edges in a path from vertex 1 to vertex N. If the path is not possible between source cell and destination cell, then return -1. Example 1: Input: K = 0 1 / 3 2 Output: 1. , a node points to one of its ancestors] present in the graph. Your task is to complete the function ShortestPath () which takes a string S and returns an array of strings containing the. Widest Path Problem | Practical application of Dijkstra's Algorithm. Approach: The idea is to use breadth first search to calculate the shortest path from source to destination. Bottom up – Start from the nodes on the bottom row; the min pathsum for these nodes are the values of the nodes themselves. Expected Time Complexity: O (R * C) Expected Auxiliary Space: O (1) Constraints: 1 <= R,C <= 103. ” in our path, we simply pop the topmost element as we have to jump back to parent’s directory. Given the following grid containing alphabets from A-Z and a string S. Time Complexity: 4^ (R*C), Here R and C are the numbers of rows and columns respectively. Given a n*m matrix, find the maximum length path (starting from any cell) such that all cells along the path are in strictly increasing order. Johnson's algorithm for All-pairs shortest paths; Shortest Path in Directed Acyclic Graph; Multistage Graph (Shortest Path) Shortest path in an unweighted graph; Karp's minimum mean (or average) weight cycle algorithm; 0-1 BFS (Shortest Path in a Binary Weight Graph) Find minimum weight cycle in an undirected graph Explanation: There exists no path from start to end. Given a Binary Tree and a number k, remove all nodes that lie only on root to leaf path (s) of length smaller than k. Example 1: Input: 1 / 2 3 a = 2, b = 3 Output: 2 Explanation: The tree formed is: 1 / 2 3 We need the distance between 2 and 3. BFS is generally used to find the Shortest Paths in the graph and the minimum distance of all nodes from Source, intermediate nodes, and Destination can be calculated by the. If the cell is out of bounds or the subproblem has already been solved, return 0 or the previously calculated value in the lookup table, respectively. Find shortest safe route in a path with landmines; Print all paths from a source point to all the 4 corners of a Matrix; Printing all solutions in N-Queen Problem; Longest path in a Matrix from a specific source cell to destination cell; Count of Possible paths of given Matrix having Bitwise XOR equal to K; Print all unique paths from given. Strings are considered a data type in general and are typically represented as arrays of bytes (or words) that store a sequence of characters. Approach: The main idea here is to use a matrix (2D array) that will keep track of the next node to point if the shortest path changes for any pair of nodes. Following is the Backtracking algorithm for Knight’s tour problem. Explanation: The first and last node of the input sequence is 1 and 4 respectively. If no valid path exists then print -1. Time Complexity: O (R * C), where R is number of rows and C are the number of columns in the given matrix. Therefore, BFS is an appropriate algorithm to solve this problem. Approach: The solution is to perform BFS or DFS to find whether there is a path or not. Shortest Path Visiting All Nodes Hard 4. So there are n stairs. Output: 0 4. There are two types of nodes to be considered. Back to Explore Page. If there is only one topological sort. Let arr [] be given set of strings. Your Task: You don't need to read input or print anything. Use induction to prove that at each stage it has given you the shortest path to the vertices visited. Complete the function shortestPath () which takes integers x and y as input parameters and returns the length of the shortest path from x to y. Our task is to Find shortest safe route in a path with landmines. Note: If the Graph contains a n Explanation: { 1, 2, 3 } is the only shortest common supersequence of {1, 2}, {1, 3} and {2, 3}. No cycle is formed, include it. You. Please Note that a and b are not always leaf node. e. Given a weighted directed graph with n nodes and m edges. Step 3: Pick edge 6-5. We one by one remove every edge from the graph, then we find the shortest path between two corner vertices of it. Example 1: Input: N=6 knightPos [ ] = {4, 5} targetPos [ ] = {1, 1} Output: 3 Explanation: Knight takes 3 step to reach from (4, 5) to (1, 1): (4, 5) -> (5, 3. Approach: The idea is to use the Shortest Path Faster Algorithm (SPFA) to find if a negative cycle is present and reachable from the. At any step i, we can move forward i, then backward i + 1. Example 1: Input: n = 3, edges. Print a given matrix in spiral form using the simulation approach: To solve the problem follow the below idea: Draw the path that the spiral makes. e. Print all paths from a given source to a destination using BFS. When it finds the first leaf node, it calls the printPath function to print the path from the leaf node to the root. Method 1. Shortest path in a directed graph by Dijkstra’s algorithm. Eulerian Circuit is an Eulerian Path which starts and ends on the same vertex. Given a path in the form of a rectangular matrix having few. The shortest path between 1 and 4 is 1 -> 3 -> 4 hence, the output is NO for the 1st example. Minimum steps to reach the target by a Knight using BFS: This problem can be seen as the shortest path in an unweighted graph. GfG-Problem Link: and Notes Link: Given two distinct words startWord and targetWord, and a list denoting wordList of unique words of equal lengths. The shortest path algorithms are the ones that focuses on calculating the minimum travelling cost from source node to destination node of a graph in optimal time and space complexities. In this post, O (ELogV) algorithm for. Practice. Below is algorithm based on set data structure. Floyd Warshall. Solve DSA problems on GfG Practice. There is a robot initially located at the top-left corner (i. Therefore the cost of the path = 3 + 5 + 4 = 12. For example, the following graph has eulerian cycle as {1, 0, 3, 4, 0, 2, 1}Input: For given graph G. Expected Time Compelxity: O (n2*log (n)) Expected Auxiliary Space: O (n2) Constraints: 1 ≤ n ≤ 500. Shortest path in a directed graph by Dijkstra’s algorithm. Find the minimum number of steps required to reach from (0,0) to (X, Y). Detailed solution for Shortest Path in Undirected Graph with unit distance: G-28 - Given an Undirected Graph having unit weight, find the shortest path from the source to all other nodes in this graph. The valid moves are: Go Top: (x, y) ——> (x – 1, y) Go. Bellman–Ford Algorithm Floyd Warshall Algorithm Johnson's algorithm for All-pairs shortest paths Shortest Path in Directed Acyclic Graph Multistage Graph. Back to Explore Page. Given a Binary Tree with all unique values and two nodes value, n1 and n2. Initialize dist [] = {INF, INF,. Approach: The idea is to use topological sorting, Follow the steps mentioned below to solve the problem: Represent the sequences in the ‘ arr [] [] ’ by a directed graph and find its topological sort order. Shortest path between two nodes in array like representation of binary tree. Here, for every vertex in the graph, we have a list of all the other vertices which the particular vertex has an edge to. 1 ≤ cost of cells ≤ 1000. For each index. Hence, if dist (a, b) is the cost of shortest path between node a and b, the required minimum cost path will be min { dist (Source, U) + dist (intermediate, U) + dist (destination, U) } for all U. Copy contents. The path from root node to node 4 is 0 -> 1 -> 3 -> 4. Step 4: Find the minimum among these edges. i. in all 4 directions. (b) Is the shortest path tree unique? (c). Shortest Path in a weighted Graph where weight of an edge is 1 or 2. Exclusively for Freshers! Participate for Free on 21st November & Fast-Track Your Resume to Top Tech Companies. Back to Explore Page. Find the shortest path from sr. In other words a node is deleted if all paths going through it have lengths smaller than k. Your task is to complete the function findShortestPath () which takes matrix as input parameter and return an integer denoting the shortest path. Find the shortest possible path to type all characters of given string in given order using only left,right,up and down movements (while staying inside the grid). This problem is mainly an extension of Find distance between two given keys of a Binary Tree. Given a weighted, directed and connected graph of V vertices and E edges, Find the shortest distance of all the vertex's from the source vertex S. Now, there arises two different cases:Given a root of binary tree and two integers startValue and destValue denoting the starting and ending node respectively. If there is no such path present then print “-1” . Push the word in the queue. Therefore, the graph contains a negative cycle. If a vertex is unreachable from the source node, then return -1 for that vertex. Find the shortest path from src(0) vertex to all the vertices and if it is impossible to reach any vertex, then return -1 for that vertex. Hence, the shortest distance. If multiple shortest supersequence exists, print any one of them. Example 1: Input: Output: 1 Explanation: 3 -> 3 is a cycle Example 2: Input: Output: 0 Explanation: no cycle in the graph. Explanation: Path is 4 2 1 3. Print path between any two nodes in a Binary Tree; Preorder Traversal of Binary Tree; Count pairs of leaf nodes in a Binary Tree which are at most K distance apart; Print all root-to-leaf paths with maximum count of even nodes; Count nodes having highest value in the path from root to itself in a Binary Tree; Height and Depth of a node in a. It shows step by step process of finding shortest paths. At each step it picks the node/cell having the lowest ‘ f ’, and process that node/cell. So “ek” becomes “geeke” which is shortest common supersequence. Replace all of the O’s in the matrix with their shortest distance from a guard, without being able to go through any walls. Simple Approach: A naive approach is to calculate the length of the longest path from every node using DFS . , they are. Initially, the cost of the shortest path is an overestimate, likened to a stretched-out spring. Let us consider another. A simple solution is to start from u, go to all adjacent vertices, and recur for adjacent vertices with k as k-1, source. For every vertex being processed, we update distances of its adjacent using distance of current vertex. Time Complexity: The time complexity of Dijkstra’s algorithm is O (V^2). Dijkstra’s algorithm is a popular algorithms for solving many single-source shortest path problems having non-negative edge weight in the graphs i. Find All possible paths from top left to bottom right. For a disconnected undirected graph, the definition is similar, a bridge is an edge removal that increases the number of disconnected components. , grid [0] [0]). Exclusively for Freshers! Participate for Free on 21st November & Fast-Track Your Resume to Top Tech Companies. Contests. While there are non-empty buckets:. Explanation: The shortest path length from 1 to N is 4, 2nd shortest length is also 4 and 3rd shortest length is 7. Expected time complexity is O (V+E). This algorithm can be used on both weighted and unweighted graphs. Therefore, if shortest paths can be found in G’, then longest paths can also be found in G. This gives the shortest path. Two cells are. Print all unique paths from given source to destination in a Matrix moving only down or right. We can. Minimum length of jumps to avoid given array of obstacles. Single source shortest path between two cities. . In the path list, for each unvisited vertex, add the copy of the path of its. You dont need to read input or print anything. You are given a weighted undirected graph having n+1 vertices numbered from 0 to n and m edges describing there are edges between a to b with some weight, find the shortest path between the vertex 1 and the vertex n, and if the path does not exist then return a list consisting of only-1. Using DFS calculate the subtree size connected to the edges. Like Prim’s MST, we generate a SPT (shortest path tree) with a given source as a root. Expected time complexity is O (V+E). Your task is to complete the function findShortestPath () which takes matrix as input parameter and return an integer denoting the shortest path. Explanation: Path is 1 2. Input: N = 5, M = 8. There is a lot to learn, Keep in mind “ Mnn bhot karega k chor yrr apne se nahi hoga ya maza. Path is:: 2 1 0 3 4 6. O ==> Open Space G ==> Guard W ==> Wall. The diagram below shows two trees each with diameter nine, the leaves that form the ends of the longest path are shaded (note that there is more than one path in each tree of length nine, but no path longer than nine nodes). Courses. Solve Problem. It has to reach the destination at (N - 1, N - 1). Here we not only find the shortest distance but also the path. Sum of weights of path between nodes 0 and 3 = 6. ​Example 2:Min cost path using Dijkstra’s algorithm: To solve the problem follow the below idea: We can also use the Dijkstra’s shortest path algorithm to find the path with minimum cost. Sum of all odd nodes in the path connecting two given nodes. Strings are defined as an array of characters. Find the length of the shortest transformation sequence from startWord to targetWord. Dijkstra’s Algorithm: It works on Non-Negative Weighted graphs. Remove nodes from Binary Tree such that sum of all remaining root-to-leaf paths is atleast K. Examp. For every index we have four options, so our overall time complexity will become 4^ (R*C). (weight, vertex). in order to generate different substring. by adding two A's at front of string. Your task is to complete the function shortestPath() which takes n vertex and m edges and vector of edges having weight as inputs and returns the shortest path between vertex 1 to n. Below are the detailed steps used in Dijkstra’s algorithm to find the shortest path from a single source vertex to all other vertices in the given graph. BFS solves single-source shortest path problems in unweightedGiven a n * m matrix grid where each element can either be 0 or 1. Problem Statement: . Given a graph and a source vertex in the graph, find the shortest paths from the source to all vertices in the given graph. Input: N = 3, M = 3, K = 2, edges = { {1, 2, 2}, {2, 3, 2}, {1, 3, 1}} Output: 1 4. Practice. This solution is usually referred to as Dijkstra’s algorithm. Method 1: Recursive. In the previous problem only going right and the bottom was allowed but in this problem, we are allowed to go bottom, up, right and left i. Input : str = "ABC". Output. The distance between the two nodes i and j will be equal to dist (i, LCA (i, j)) + dist (j, LCA (i. step 2 : We find. Example 1: Input: 1 / 2 3 Output: 1 2 #1 3 # ExplanatFollow the steps below to solve the problem: Initialize a variable, say res, to store all possible shortest paths. It follows Greedy Approach. The difference. Expected Time Complexity: O (R * C) Expected Auxiliary Space: O (1) Constraints: 1 <= R,C <= 103. Algorithm: Steps involved in finding the topological ordering of a DAG: Step-1: Compute in-degree (number of incoming edges) for each of the vertex present in the DAG and initialize the count of visited nodes as 0. Find shortest safe route in a path with landmines; Print all paths from a source point to all the 4 corners of a Matrix; Printing all solutions in N-Queen Problem; Longest path in a Matrix from a specific source cell to destination cell; Count of Possible paths of given Matrix having Bitwise XOR equal to K; Print all unique paths from given. The allowed moves are moving a cell left (L), right (R), up (U), and. Python3. Dijkstra’s shortest path for adjacency matrix representation. The faster one is called the fast pointer and the. To solve the problem, we need to try out all intermediate vertices ranging [1, N] and check: If there is a direct edge already which exists between the two nodes. Another method: It can be solved in polynomial time with the help of Breadth First Search. Output: Sort the nodes in a topological way. Shortest path from 1 to n | Practice | GeeksforGeeks. If there is no possible path, return -1. Follow the steps below to solve the problem: If the current cell is out of the boundary, then return. Below is the implementation of the approach. Shortest path from a source cell to a destination cell of a Binary Matrix through cells consisting only of 1s. Shortest Path Revisited. Expected Time complexity is O (MN) for a M x N matrix. Practice. Approach: The problem can be solved by the Dijkstra algorithm. The problem is to find the shortest distances between every pair of vertices in a given edge-weighted directed graph. Complete the function booleanMatrix () that takes the matrix as input parameter and modifies it in-place. Read. Now when we are at leaf node and it is equal to arr [index] and there is no further element in given sequence of root to leaf path, this means that path exist in given tree. For example, consider the below graph. For example consider the below graph. Assume that we need to find reachable nodes for n nodes, the time complexity for this solution would be O (n* (V+E)) where V is number of nodes in the graph and E is number of edges in the graph. Note: If the Graph contains a nExplanation: { 1, 2, 3 } is the only shortest common supersequence of {1, 2}, {1, 3} and {2, 3}. Since distance of + 5 and – 5 from 0 is same, hence we find answer for absolute value of destination. Example 1: Input: V = 2 adj [] = { { {1, 9}}, { {0, 9}}} S = 0 Output: 0 9 Explanation: The source vertex is 0. Output. There is an edge from a vertex i to a vertex j iff either j = i + 1 or j = 3 * i. Contests. Follow. e. } and dist [s] = 0 where s is the source. e. Note: It is assumed that negative cost cycles do not exist in input matrix. Insert non-lcs characters (in their original order in strings) to the lcs found above, and return the result. a) Extract minimum distance vertex from Set. If a node X lies on multiple root-to-leaf paths and if any of the paths has path length >= k, then X is not deleted from Binary Tree. Note: The initial and the target position coordinates of Knight have been given according to 1-base indexing. , str [n-1] of str has. At the time of BFS maintain an array of distance [n] and initialize it to zero for all vertices. ; Initialise a priority-queue pq with S and its weight as 1 and a visited array v[]. This gives the shortest path. def BFS_SP (graph, start,. Initialize an unordered_map, say adj to store the edges. It is a single source shortest path algorithm. The red cells are blocked, white cell denotes the path and the green cells are not blocked cells. Initially, this set is empty. A shortest path from S to X must have its next-to-last vertex in S . dp [i] [j] represents shortest path from i to j. Approach: Use recursion to move first right then down from each cell in the path of the matrix mat[][], starting from source, and store each value in a vector. Else, discard it. Nodes are labeled from 0 to n-1, the task is to check if it contains a negative weight cycle or not. Find the shortest path from src(0) vertex to all the vertices and if it is impossible to reach any vertex, then return -1 for that vertex. If it is unreachable then return -1. In normal BFS of a graph, all edges have equal weight but in 0-1 BFS some edges may have 0 weight and some may have 1 weight. Here, for every vertex in the graph, we have a list of all the other vertices which the particular vertex has an edge to. Dijkstra. The sum of weight in the above path is -3 + 2 – 1 = -2. first n characters in input string. of arr [] to temp [] 2) While temp [] contains more than one strings. 0-1 BFS (Shortest Path in a Binary Weight Graph) Shortest path between two nodes in array like representation of binary tree. Time Complexity: O (N), the time complexity of this algorithm is O (N), where N is the number of nodes in the tree. e. of arr [] to temp [] 2) While temp [] contains more than one strings. You don't need to read input or print anything. In this problem statement, we have assumed the source vertex to be ‘0’. If a graph contains a. Output: “L”. e. "contribute", "practice"} word1 = "geeks" word2 = "practice" Output: 2 Explanation: Minimum distance between the words "geeks" and "practice" is 2. Given a DAG, print all topological sorts of the graph. Below is a recursive solution suggested by Arpit Thapar here . Nodes are labeled from 0 to n-1, the task is to check if it contains a negative weight cycle or not. This problem is an extension of problem: Min Cost Path with right and bottom moves allowed. Create an empty queue and enqueue the source cell having a distance 0 from source (itself) and mark it as visited.