 # How Do You Find The Shortest Path In BFS?

## Is Dijkstra BFS or DFS?

You can implement Dijkstra’s algorithm as BFS with a priority queue (though it’s not the only implementation).

Dijkstra’s algorithm relies on the property that the shortest path from s to t is also the shortest path to any of the vertices along the path.

This is exactly what BFS does.

Exactly like BFS..

## What is the difference between DFS and BFS?

DFS, stands for Depth First Search. BFS uses Queue to find the shortest path. DFS uses Stack to find the shortest path. BFS is better when target is closer to Source.

## How many shortest paths are there?

There are two shortest paths algorithms known as Dijkstra’s algorithm, depending on whether a vertex can be enqueued on the priority queue more than once.

## Can DFS be used to find shortest path?

No, you cannot use DFS to find shortest path in an unweighted graph. It is not the case that, finding the shortest path between two nodes is exclusively solved by BFS. In an unweighted graph the shortest path are the smallest number of edges that must be traversed from source to destination nodes.

## What are the applications of BFS and DFS?

Using GPS navigation system BFS is used to find neighboring places. In networking, when we want to broadcast some packets, we use the BFS algorithm. Path finding algorithm is based on BFS or DFS. BFS is used in Ford-Fulkerson algorithm to find maximum flow in a network.

## How do you find the shortest path between two vertices?

Algorithm to find the shortest path between two vertices in an undirected graphInput the graph.Input the source and destination nodes.Find the paths between the source and the destination nodes.Find the number of edges in all the paths and return the path having the minimum number of edges.

## How do you determine the number of shortest paths?

Use BFS to determine the length of the shortest v-w-path. Then use DFS to find the number of the v-w-shortest paths such that two nodes are connected and the length of path equals to the output of BFS.

## What do you mean by shortest path?

(classic problem) Definition: The problem of finding the shortest path in a graph from one vertex to another. “Shortest” may be least number of edges, least total weight, etc. Also known as single-pair shortest-path problem.

## Why does BFS find the shortest path?

The BFS will first visit nodes with distance 0 then all nodes with distance 1 and so on. This property is the reason why we can use a BFS to find the shortest path even in cyclic graphs.

## Which algorithm helps to find the shortest path in an unweighted graph?

BFSWe say that BFS is the algorithm to use if we want to find the shortest path in an undirected, unweighted graph. The claim for BFS is that the first time a node is discovered during the traversal, that distance from the source would give us the shortest path.

## Why BFS takes more memory than DFS?

For implementation, BFS uses a queue data structure, while DFS uses a stack. BFS uses a larger amount of memory because it expands all children of a vertex and keeps them in memory. It stores the pointers to a level’s child nodes while searching each level to remember where it should go when it reaches a leaf node.

## What is DFS and BFS with examples?

BFS vs DFS BFS stands for Breadth First Search. DFS stands for Depth First Search. 2. BFS(Breadth First Search) uses Queue data structure for finding the shortest path. DFS(Depth First Search) uses Stack data structure.

## How do you find the shortest path in an unweighted graph?

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. One solution is to solve in O(VE) time using Bellman–Ford. If there are no negative weight cycles, then we can solve in O(E + VLogV) time using Dijkstra’s algorithm.

## Which algorithm is used to find shortest path?

Dijkstra’s algorithmDijkstra’s algorithm (or Dijkstra’s Shortest Path First algorithm, SPF algorithm) is an algorithm for finding the shortest paths between nodes in a graph, which may represent, for example, road networks. It was conceived by computer scientist Edsger W. Dijkstra in 1956 and published three years later.