Number of Ways to Arrive at Destination | Straight Forward Simple | Leetcode 1976 | codestorywithMIK

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Dijkstra's Algorithm | PART-1 -    • Dijkstra's Algorithm | PART-1 | Graph Conc...  
Dijkstra's Algorithm | PART-2 -    • Dijkstra's Algorithm | PART-2 | (Microsoft...  

Hi Everyone, this is the 72nd video of our Playlist "Graphs : Popular Interview Problems".
Now we will be solving a good Graph practice problem on Dijkstra's Algorithm - Number of Ways to Arrive at Destination | Straight Forward Simple | Leetcode 1976 | codestorywithMIK

We will see how simply this is nothing but Dijkstra's Algorithm with one slight change to count the paths.

Problem Name : Number of Ways to Arrive at Destination | Straight Forward Simple | Leetcode 1976 | codestorywithMIK
Company Tags : will update later
My solutions on Github(C++ & JAVA) - github.com/MAZHARMIK/Interview_DS_Algo/blob/master…
Leetcode Link : leetcode.com/problems/number-of-ways-to-arrive-at-…


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Video Summary :
The approach uses Dijkstra's algorithm with a priority queue to find the shortest path from node 0 to node n−1 in a weighted graph. An adjacency list represents the graph, and a min-heap (priority queue) helps process nodes in increasing order of travel time.
A result array stores the shortest time to reach each node, and a pathCount array keeps track of the number of shortest paths to each node. Initially, the distance to node 0 is set to 0, and its path count is 1.
For each node processed, its neighbors are checked. If a shorter path is found, the shortest time is updated, and the path count is set to match the current node’s path count. If an equal shortest time is found, the number of ways to reach that node is updated modulo 10^9+7.
The algorithm efficiently finds the number of shortest paths using Dijkstra’s greedy approach combined with dynamic programming principles.


✨ Timelines✨
00:00 - Introduction
0:28 - Motivation
1:05 - Problem Explanation
5:23 - Why Dijkstra's Algorithm
5:51 - Jor se Bolo Dijkstra's Algorithm
6:26 - Recap Dijkstra's Algorithm
9:53 - Small Example Dry Run
22:42 - Coding it up
30:20 - Homework

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