Added the Solution of Tuple with same product - Issue No #1196

dsa-problems/leetcode-problems/1600-1699.md

@@ -200,7 +200,7 @@ export const problems = [
         "problemName": "1631. Path With Minimum Effort",
         "difficulty": "Medium",
         "leetCodeLink": "https://leetcode.com/problems/path-with-minimum-effort",
-        "solutionLink": "#"
+        "solutionLink": "/dsa-solutions/lc-solutions/1600-1699/path-with-minimum-effort"
     },
     {
         "problemName": "1632. Rank Transform of a Matrix",

dsa-problems/leetcode-problems/1700-1799.md

@@ -170,7 +170,7 @@ export const problems = [
         "problemName": "1726. Tuple with Same Product",
         "difficulty": "Medium",
         "leetCodeLink": "https://leetcode.com/problems/tuple-with-same-product",
-        "solutionLink": "#"
+        "solutionLink": "/dsa-solutions/lc-solutions/1700-1799/tuple-with-same-product"
     },
     {
         "problemName": "1727. Largest Submatrix With Rearrangements",

dsa-problems/leetcode-problems/1800-1899.md

@@ -242,7 +242,7 @@ export const problems = [
     "problemName": "1838. Frequency of the Most Frequent Element",
     "difficulty": "Medium",
     "leetCodeLink": "https://leetcode.com/problems/frequency-of-the-most-frequent-element",
-    "solutionLink": "#"
+    "solutionLink": "/dsa-solutions/lc-solutions/1800-1899/frequency-of-the-most-frequent-element"
   },
   {
     "problemName": "1839. Longest Substring Of All Vowels in Order",

dsa-solutions/lc-solutions/1600-1699/1631-path-with-minimum-effort.md

@@ -0,0 +1,352 @@
+---
+id: path-with-minimum-effort
+title:  Path With Minimum Effort
+sidebar_label: 1631 - Path With Minimum Effort
+tags:
+- Array
+- Binary Search
+- Depth-First Search
+- Breadth-First Search
+- Union Find
+- Heap (Priority Queue)
+- Matrix
+
+description: "This is a solution to the Path With Minimum Effort problem on LeetCode."
+---
+
+## Problem Description
+You are a hiker preparing for an upcoming hike. You are given heights, a 2D array of size rows x columns, where `heights[row][col]` represents the height of cell (row, col). You are situated in the top-left cell, `(0, 0)`, and you hope to travel to the bottom-right cell, `(rows-1, columns-1) (i.e., 0-indexed)`. You can move up, down, left, or right, and you wish to find a route that requires the minimum effort.
+
+A route's effort is the maximum absolute difference in heights between two consecutive cells of the route.
+
+Return the minimum effort required to travel from the top-left cell to the bottom-right cell.
+
+
+### Examples
+
+**Example 1:**
+![image](https://assets.leetcode.com/uploads/2020/10/04/ex1.png)
+
+```
+Input: heights = [[1,2,2],[3,8,2],[5,3,5]]
+Output: 2
+Explanation: The route of [1,3,5,3,5] has a maximum absolute difference of 2 in consecutive cells.
+This is better than the route of [1,2,2,2,5], where the maximum absolute difference is 3.
+
+```
+
+**Example 2:**
+![image](https://assets.leetcode.com/uploads/2020/10/04/ex2.png)
+
+```
+Input: heights = [[1,2,3],[3,8,4],[5,3,5]]
+Output: 1
+Explanation: The route of [1,2,3,4,5] has a maximum absolute difference of 1 in consecutive cells, which is better than route [1,3,5,3,5].
+```
+
+**Example 3:**
+![image](https://assets.leetcode.com/uploads/2020/10/04/ex3.png)
+```
+Input: heights = [[1,2,1,1,1],[1,2,1,2,1],[1,2,1,2,1],[1,2,1,2,1],[1,1,1,2,1]]
+Output: 0
+Explanation: This route does not require any effort.
+```
+
+### Constraints
+- `rows == heights.length`
+- `columns == heights[i].length`
+- `1 <= rows, columns <= 100`
+- `1 <= heights[i][j] <= 10^6`
+
+## Solution for Path With Minimum Effort Problem
+### Approach 
+#### Dijkstra's Algorithm:
+-  A classic algorithm for finding the shortest path in a weighted graph, adapted for this problem.
+
+#### Steps
+##### Initialize Priority Queue:
+- The algorithm starts at the top-left corner (the source). The priority queue is initialized to store the effort needed to reach each cell from the source. The effort for the source itself is zero.
+##### Distance Matrix:
+- A 2D array keeps track of the minimum effort required to reach each cell. Initially, this is set to infinity for all cells except the source.
+
+##### Iterate and Update Distances:
+- The algorithm pops the cell with the smallest effort from the priority queue and explores its neighbors. The effort required to reach a neighbor is updated if a smaller effort is found.
+##### Early Exit:
+- The algorithm stops when it reaches the bottom-right corner, returning the effort required to get there.
+
+
+<Tabs>
+  <TabItem value="Solution" label="Solution">
+
+    #### Implementation
+    ```jsx live
+    function Solution(arr) {
+      function minimumEffortPath(heights) {
+       const rows = heights.length, cols = heights[0].length;
+        const dist = Array.from(Array(rows), () => Array(cols).fill(Infinity));
+        const minHeap = [[0, 0, 0]];  // [effort, x, y]
+
+        dist[0][0] = 0;
+        const directions = [[0, 1], [0, -1], [1, 0], [-1, 0]];
+
+        while (minHeap.length > 0) {
+            const [effort, x, y] = minHeap.shift();
+
+            if (effort > dist[x][y]) continue;
+
+            if (x === rows - 1 && y === cols - 1) return effort;
+
+            for (const [dx, dy] of directions) {
+                const nx = x + dx, ny = y + dy;
+                if (nx >= 0 && nx < rows && ny >= 0 && ny < cols) {
+                    const newEffort = Math.max(effort, Math.abs(heights[x][y] - heights[nx][ny]));
+                    if (newEffort < dist[nx][ny]) {
+                        dist[nx][ny] = newEffort;
+                        minHeap.push([newEffort, nx, ny]);
+                        minHeap.sort((a, b) => a[0] - b[0]);
+                    }
+                }
+            }
+        }
+        return -1;
+    }
+      const input = [[1,2,2],[3,8,2],[5,3,5]]
+      const output = minimumEffortPath(input) ;
+      return (
+        <div>
+          <p>
+            <b>Input: </b>
+            {JSON.stringify(input)}
+          </p>
+          <p>
+            <b>Output:</b> {output.toString()}
+          </p>
+        </div>
+      );
+    }
+    ```
+
+    #### Complexity Analysis
+
+    - Time Complexity: $ O(M*N log(M*N)) $ where M and N are the dimensions of the grid. This is primarily due to the operations on the priority queue.
+    - Space Complexity: $ O(M*N) $ $O(M*N)$, needed for the distance matrix and the priority queue.
+
+   ## Code in Different Languages
+   <Tabs>
+  <TabItem value="JavaScript" label="JavaScript">
+  <SolutionAuthor name="@hiteshgahanolia"/>
+   ```javascript
+     function minimumEffortPath(heights) {
+       const rows = heights.length, cols = heights[0].length;
+        const dist = Array.from(Array(rows), () => Array(cols).fill(Infinity));
+        const minHeap = [[0, 0, 0]];  // [effort, x, y]
+
+        dist[0][0] = 0;
+        const directions = [[0, 1], [0, -1], [1, 0], [-1, 0]];
+
+        while (minHeap.length > 0) {
+            const [effort, x, y] = minHeap.shift();
+
+            if (effort > dist[x][y]) continue;
+
+            if (x === rows - 1 && y === cols - 1) return effort;
+
+            for (const [dx, dy] of directions) {
+                const nx = x + dx, ny = y + dy;
+                if (nx >= 0 && nx < rows && ny >= 0 && ny < cols) {
+                    const newEffort = Math.max(effort, Math.abs(heights[x][y] - heights[nx][ny]));
+                    if (newEffort < dist[nx][ny]) {
+                        dist[nx][ny] = newEffort;
+                        minHeap.push([newEffort, nx, ny]);
+                        minHeap.sort((a, b) => a[0] - b[0]);
+                    }
+                }
+            }
+        }
+        return -1;
+    }   
+    ```
+
+  </TabItem>
+  <TabItem value="TypeScript" label="TypeScript">
+  <SolutionAuthor name="@hiteshgahanolia"/> 
+   ```typescript
+   class Solution {
+    minimumEffortPath(heights: number[][]): number {
+        const pq = new MinPriorityQueue<{priority: number, element: [number, [number, number]]}>({ priority: x => x.priority });
+        const n = heights.length;
+        const m = heights[0].length;
+        const dist = Array.from({ length: n }, () => Array(m).fill(Infinity));
+        dist[0][0] = 0;
+        pq.enqueue({priority: 0, element: [0, [0, 0]]});
+
+        const delRow = [-1, 0, 1, 0];
+        const delCol = [0, 1, 0, -1];
+
+        while (!pq.isEmpty()) {
+            const {element: [diff, [row, col]]} = pq.dequeue();
+
+            if (row === n - 1 && col === m - 1) return diff;
+
+            for (let i = 0; i < 4; i++) {
+                const newRow = row + delRow[i];
+                const newCol = col + delCol[i];
+
+                if (newRow >= 0 && newRow < n && newCol >= 0 && newCol < m) {
+                    const newEffort = Math.max(Math.abs(heights[row][col] - heights[newRow][newCol]), diff);
+                    if (newEffort < dist[newRow][newCol]) {
+                        dist[newRow][newCol] = newEffort;
+                        pq.enqueue({priority: newEffort, element: [newEffort, [newRow, newCol]]});
+                    }
+                }
+            }
+        }
+        return 0;
+    }
+}
+
+    ```
+  </TabItem>
+  <TabItem value="Python" label="Python">
+  <SolutionAuthor name="@hiteshgahanolia"/>
+   ```python
+   import heapq
+
+class Solution:
+    def minimumEffortPath(self, heights: List[List[int]]) -> int:
+        n, m = len(heights), len(heights[0])
+        dist = [[float('inf')] * m for _ in range(n)]
+        dist[0][0] = 0
+        pq = [(0, 0, 0)]
+
+        delRow = [-1, 0, 1, 0]
+        delCol = [0, 1, 0, -1]
+
+        while pq:
+            diff, row, col = heapq.heappop(pq)
+
+            if row == n - 1 and col == m - 1:
+                return diff
+
+            for i in range(4):
+                newRow, newCol = row + delRow[i], col + delCol[i]
+
+                if 0 <= newRow < n and 0 <= newCol < m:
+                    newEffort = max(abs(heights[row][col] - heights[newRow][newCol]), diff)
+                    if newEffort < dist[newRow][newCol]:
+                        dist[newRow][newCol] = newEffort
+                        heapq.heappush(pq, (newEffort, newRow, newCol))
+        return 0
+
+    ```
+
+  </TabItem>
+  <TabItem value="Java" label="Java">
+  <SolutionAuthor name="@hiteshgahanolia"/>
+   ```java
+   import java.util.*;
+
+class Solution {
+    public int minimumEffortPath(int[][] heights) {
+        PriorityQueue<int[]> pq = new PriorityQueue<>(Comparator.comparingInt(a -> a[0]));
+        int n = heights.length;
+        int m = heights[0].length;
+        int[][] dist = new int[n][m];
+        for (int[] row : dist) Arrays.fill(row, Integer.MAX_VALUE);
+        dist[0][0] = 0;
+        pq.offer(new int[]{0, 0, 0});
+
+        int[] delRow = {-1, 0, 1, 0};
+        int[] delCol = {0, 1, 0, -1};
+
+        while (!pq.isEmpty()) {
+            int[] curr = pq.poll();
+            int diff = curr[0];
+            int row = curr[1];
+            int col = curr[2];
+
+            if (row == n - 1 && col == m - 1) return diff;
+
+            for (int i = 0; i < 4; i++) {
+                int newRow = row + delRow[i];
+                int newCol = col + delCol[i];
+
+                if (newRow >= 0 && newRow < n && newCol >= 0 && newCol < m) {
+                    int newEffort = Math.max(Math.abs(heights[row][col] - heights[newRow][newCol]), diff);
+                    if (newEffort < dist[newRow][newCol]) {
+                        dist[newRow][newCol] = newEffort;
+                        pq.offer(new int[]{newEffort, newRow, newCol});
+                    }
+                }
+            }
+        }
+        return 0;
+    }
+}
+
+    ```
+
+  </TabItem>
+  <TabItem value="C++" label="C++">
+  <SolutionAuthor name="@hiteshgahanolia"/>
+   ```cpp
+   class Solution {
+public:
+    int minimumEffortPath(vector<vector<int>>& heights) {
+        priority_queue<pair<int, pair<int, int>>,
+                       vector<pair<int, pair<int, int>>>,
+                       greater<pair<int, pair<int, int>>>>pq;
+
+        int n = heights.size();
+        int m = heights[0].size();
+
+        vector<vector<int>> dist(n, vector<int>(m, 1e9));
+        dist[0][0] = 0;
+        // {diff{row,col}}
+        pq.push({0, {0, 0}});
+
+        int delRow[] = {-1, 0, 1, 0};
+        int delCol[] = {0, 1, 0, -1};
+
+        while (!pq.empty()) {
+            auto it = pq.top();
+            pq.pop();
+
+            int diff = it.first;
+            int row = it.second.first;
+            int col = it.second.second;
+
+            if (row == n - 1 && col == m - 1)
+                return diff;
+
+            for (int i = 0; i < 4; i++) {
+                int newRow = row + delRow[i];
+                int newCol = col + delCol[i];
+
+                if (newRow >= 0 & newRow < n && newCol >= 0 && newCol < m) {
+                    int newEffort = max(
+                        abs(heights[row][col] - heights[newRow][newCol]), diff);
+                    ;
+                    if (newEffort < dist[newRow][newCol]) {
+                        dist[newRow][newCol] = newEffort;
+                        pq.push({newEffort, {newRow, newCol}});
+                    }
+                }
+            }
+        }
+        return 0;
+    }
+};
+    ```
+</TabItem>
+</Tabs>
+
+  </TabItem>
+</Tabs>
+
+## References
+
+- **LeetCode Problem**: [Path With Minimum Effort](https://leetcode.com/problems/path-with-minimum-effort/description/)
+
+- **Solution Link**: [LeetCode Solution](https://leetcode.com/problems/path-with-minimum-effort/solutions)
+