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Rod Cutting

Last Updated : 02 Dec, 2024
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Given a rod of length n inches and an array price[]. price[i] denotes the value of a piece of length i. The task is to determine the maximum value obtainable by cutting up the rod and selling the pieces.

Note: price[] is 1-indexed array.

Input: price[] = [1, 5, 8, 9, 10, 17, 17, 20]
Output: 22
Explanation: The maximum obtainable value is 22 by cutting in two pieces of lengths 2 and 6, i.e., 5 + 17 = 22.

Input : price[] = [3, 5, 8, 9, 10, 17, 17, 20]
Output : 24
Explanation : The maximum obtainable value is 24 by cutting the rod into 8 pieces of length 1, i.e, 8*price[1]= 8*3 = 24.

Input : price[] = [3]
Output : 3
Explanation: There is only 1 way to pick a piece of length 1.

Table of Content

  • Using Recursion – O(n^n) Time and O(n) Space
  • Using Top-Down DP (Memoization) - O(n^2) Time and O(n) Space
  • Using Bottom-Up DP (Tabulation) - O(n^2) Time and O(n) Space
  • Using the idea of Unbounded Knapsack - O(n^2) time and O(n^2) space

Using Recursion - O(n^n) Time and O(n) Space

The recursive approach involves solving the problem by considering all possible ways to cut the rod into two pieces at every length j (where 1<=j<=i), calculating the profit for each cut, and finding the maximum profit among these options. At each step, the rod of length i is divided into two parts: j and i - j. The profit from this cut is the sum of the price of the piece of length j (given as price[j-1]) and the maximum profit obtainable from the remaining rod of length i-j (computed recursively). The base case for this recursion is when i equals 0, where the maximum profit is simply 0.

The recurrence relation will be:

  • cutRod(i) = max(price[j-1] + cutRod(i-j)) for (1<=j<=i)

Base Case:
If i == 0, return 0.

C++
// C++ program to find maximum // profit from rod of size n  #include <bits/stdc++.h> using namespace std;  int cutRodRecur(int i, vector<int> &price) {          // Base case     if (i==0) return 0;          int ans = 0;          // Find maximum value for each cut.     // Take value of rod of length j, and      // recursively find value of rod of      // length (i-j).     for (int j=1; j<=i; j++) {         ans = max(ans, price[j-1]+cutRodRecur(i-j, price));     }          return ans; }  int cutRod(vector<int> &price) {     int n = price.size();          return cutRodRecur(n, price); }  int main() {     vector<int> price =  { 1, 5, 8, 9, 10, 17, 17, 20};     cout << cutRod(price);     return 0; } 
Java
// Java program to find maximum // profit from rod of size n  import java.util.*;  class GfG {      static int cutRodRecur(int i, int[] price) {                  // Base case         if (i == 0) return 0;                  int ans = 0;          // Find maximum value for each cut.         // Take value of rod of length j, and          // recursively find value of rod of          // length (i-j).         for (int j = 1; j <= i; j++) {             ans = Math.max(ans, price[j - 1] + cutRodRecur(i - j, price));         }          return ans;     }      static int cutRod(int[] price) {         int n = price.length;          return cutRodRecur(n, price);     }      public static void main(String[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         System.out.println(cutRod(price));     } } 
Python
# Python program to find maximum # profit from rod of size n   def cutRodRecur(i, price):          # Base case     if i == 0:         return 0          ans = 0      # Find maximum value for each cut.     # Take value of rod of length j, and      # recursively find value of rod of      # length (i-j).     for j in range(1, i + 1):         ans = max(ans, price[j - 1] + cutRodRecur(i - j, price))      return ans  def cutRod(price):     n = len(price)      return cutRodRecur(n, price)  if __name__ == "__main__":     price = [1, 5, 8, 9, 10, 17, 17, 20]     print(cutRod(price)) 
C#
// C# program to find maximum // profit from rod of size n   using System;  class GfG {      static int cutRodRecur(int i, int[] price) {                  // Base case         if (i == 0) return 0;                  int ans = 0;          // Find maximum value for each cut.         // Take value of rod of length j, and          // recursively find value of rod of          // length (i-j).         for (int j = 1; j <= i; j++) {             ans = Math.Max(ans, price[j - 1] + cutRodRecur(i - j, price));         }          return ans;     }      static int cutRod(int[] price) {         int n = price.Length;          return cutRodRecur(n, price);     }      static void Main(string[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         Console.WriteLine(cutRod(price));     } } 
JavaScript
// JavaScript program to find maximum // profit from rod of size n   function cutRodRecur(i, price) {          // Base case     if (i === 0) return 0;          let ans = 0;      // Find maximum value for each cut.     // Take value of rod of length j, and      // recursively find value of rod of      // length (i-j).     for (let j = 1; j <= i; j++) {         ans = Math.max(ans, price[j - 1] + cutRodRecur(i - j, price));     }      return ans; }  function cutRod(price) {     const n = price.length;      return cutRodRecur(n, price); }  const price = [1, 5, 8, 9, 10, 17, 17, 20]; console.log(cutRod(price)); 

Output
22

Using Top-Down DP (Memoization) - O(n^2) Time and O(n) Space

If we notice carefully, we can observe that the above recursive solution holds the following two properties of Dynamic Programming:

1. Optimal Substructure: Maximum profit at index i, i.e., cutRod(i), depends on the optimal solutions of the subproblems cutRod(i-1) , cutRod(i-2), ..., cutRod(0) . By comparing these optimal substructures, we can efficiently calculate the maximum profit at index i.

2. Overlapping Subproblems: While applying a recursive approach in this problem, we notice that certain subproblems are computed multiple times.

  • There is only 1 parameter: i that changes in the recursive solution. So we create a 1D array of size n for memoization.
  • We initialize this array as -1 to indicate nothing is computed initially.
  • Now we modify our recursive solution to first check if the value is -1, then only make recursive calls. This way, we avoid re-computations of the same subproblems.
C++
// C++ program to find maximum // profit from rod of size n  #include <bits/stdc++.h> using namespace std;  int cutRodRecur(int i, vector<int> &price, vector<int> &memo) {          // Base case     if (i==0) return 0;          // If value is memoized     if (memo[i-1]!=-1) return memo[i-1];          int ans = 0;          // Find maximum value for each cut.     // Take value of rod of length j, and      // recursively find value of rod of      // length (i-j).     for (int j=1; j<=i; j++) {         ans = max(ans, price[j-1]+cutRodRecur(i-j, price, memo));     }          return memo[i-1] = ans; }  int cutRod(vector<int> &price) {     int n = price.size();     vector<int> memo(price.size(), -1);     return cutRodRecur(n, price, memo); }  int main() {     vector<int> price =  { 1, 5, 8, 9, 10, 17, 17, 20};     cout << cutRod(price);     return 0; } 
Java
// Java program to find maximum // profit from rod of size n   import java.util.*;  class GfG {      static int cutRodRecur(int i, int[] price, int[] memo) {                  // Base case         if (i == 0) return 0;                  // If value is memoized         if (memo[i - 1] != -1) return memo[i - 1];                  int ans = 0;          // Find maximum value for each cut.         // Take value of rod of length j, and          // recursively find value of rod of          // length (i-j).         for (int j = 1; j <= i; j++) {             ans = Math.max(ans, price[j - 1] + cutRodRecur(i - j, price, memo));         }          return memo[i - 1] = ans;     }      static int cutRod(int[] price) {         int n = price.length;         int[] memo = new int[n];         Arrays.fill(memo, -1);         return cutRodRecur(n, price, memo);     }      public static void main(String[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         System.out.println(cutRod(price));     } } 
Python
# Python program to find maximum # profit from rod of size n   def cutRodRecur(i, price, memo):          # Base case     if i == 0:         return 0          # If value is memoized     if memo[i - 1] != -1:         return memo[i - 1]          ans = 0      # Find maximum value for each cut.     # Take value of rod of length j, and      # recursively find value of rod of      # length (i-j).     for j in range(1, i + 1):         ans = max(ans, price[j - 1] + cutRodRecur(i - j, price, memo))      memo[i - 1] = ans     return ans  def cutRod(price):     n = len(price)     memo = [-1] * n     return cutRodRecur(n, price, memo)  if __name__ == "__main__":     price = [1, 5, 8, 9, 10, 17, 17, 20]     print(cutRod(price)) 
C#
// C# program to find maximum // profit from rod of size n   using System;  class GfG {      static int cutRodRecur(int i, int[] price, int[] memo) {                  // Base case         if (i == 0) return 0;                  // If value is memoized         if (memo[i - 1] != -1) return memo[i - 1];                  int ans = 0;          // Find maximum value for each cut.         // Take value of rod of length j, and          // recursively find value of rod of          // length (i-j).         for (int j = 1; j <= i; j++) {             ans = Math.Max(ans, price[j - 1] +             cutRodRecur(i - j, price, memo));         }          return memo[i - 1] = ans;     }      static int cutRod(int[] price) {         int n = price.Length;         int[] memo = new int[n];         Array.Fill(memo, -1);         return cutRodRecur(n, price, memo);     }      static void Main(string[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         Console.WriteLine(cutRod(price));     } } 
JavaScript
// JavaScript program to find maximum // profit from rod of size n   function cutRodRecur(i, price, memo) {          // Base case     if (i === 0) return 0;          // If value is memoized     if (memo[i - 1] !== -1) return memo[i - 1];          let ans = 0;      // Find maximum value for each cut.     // Take value of rod of length j, and      // recursively find value of rod of      // length (i-j).     for (let j = 1; j <= i; j++) {         ans = Math.max(ans, price[j - 1] + cutRodRecur(i - j, price, memo));     }      memo[i - 1] = ans;     return ans; }  function cutRod(price) {     const n = price.length;     const memo = Array(n).fill(-1);     return cutRodRecur(n, price, memo); }  const price = [1, 5, 8, 9, 10, 17, 17, 20]; console.log(cutRod(price)); 

Output
22

Using Bottom-Up DP (Tabulation) - O(n^2) Time and O(n) Space

The idea is to fill the dp table from bottom to up. For each rod of length i, starting from i = 1 to i = n, find the maximum value that can obtained by cutting it into two pieces of length j and (i-j).

C++
// C++ program to find maximum // profit from rod of size n  #include <bits/stdc++.h> using namespace std;  int cutRod(vector<int> &price) {     int n = price.size();     vector<int> dp(price.size()+1, 0);          // Find maximum value for all      // rod of length i.     for (int i=1; i<=n; i++) {         for (int j=1; j<=i; j++) {             dp[i] = max(dp[i], price[j-1]+dp[i-j]);         }     }          return dp[n]; }  int main() {     vector<int> price =  { 1, 5, 8, 9, 10, 17, 17, 20};     cout << cutRod(price);     return 0; } 
Java
// Java program to find maximum // profit from rod of size n   import java.util.*;  class GfG {      static int cutRod(int[] price) {         int n = price.length;         int[] dp = new int[n + 1];          // Find maximum value for all          // rod of length i.         for (int i = 1; i <= n; i++) {             for (int j = 1; j <= i; j++) {                 dp[i] = Math.max(dp[i], price[j - 1] + dp[i - j]);             }         }          return dp[n];     }      public static void main(String[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         System.out.println(cutRod(price));     } } 
Python
# Python program to find maximum # profit from rod of size n   def cutRod(price):     n = len(price)     dp = [0] * (n + 1)      # Find maximum value for all      # rod of length i.     for i in range(1, n + 1):         for j in range(1, i + 1):             dp[i] = max(dp[i], price[j - 1] + dp[i - j])      return dp[n]  if __name__ == "__main__":     price = [1, 5, 8, 9, 10, 17, 17, 20]     print(cutRod(price)) 
C#
// C# program to find maximum // profit from rod of size n   using System;  class GfG {      static int cutRod(int[] price) {         int n = price.Length;         int[] dp = new int[n + 1];          // Find maximum value for all          // rod of length i.         for (int i = 1; i <= n; i++) {             for (int j = 1; j <= i; j++) {                 dp[i] = Math.Max(dp[i], price[j - 1] + dp[i - j]);             }         }          return dp[n];     }      static void Main(string[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         Console.WriteLine(cutRod(price));     } } 
JavaScript
// JavaScript program to find maximum // profit from rod of size n   function cutRod(price) {     const n = price.length;     const dp = Array(n + 1).fill(0);      // Find maximum value for all      // rod of length i.     for (let i = 1; i <= n; i++) {         for (let j = 1; j <= i; j++) {             dp[i] = Math.max(dp[i], price[j - 1] + dp[i - j]);         }     }      return dp[n]; }  const price = [1, 5, 8, 9, 10, 17, 17, 20]; console.log(cutRod(price)); 

Output
22

Using the idea of Unbounded Knapsack - O(n^2) time and O(n^2) space

This problem is very similar to the Unbounded Knapsack Problem, where there are multiple occurrences of the same item. Here we consider length of rod as capacity of knapsack. All lengths from 1 to n are considered as weights of items and prices as values of items.

C++
// C++ program to find maximum // profit from rod of size n  #include <bits/stdc++.h> using namespace std;  // Find the maximum value obtainable from rod  // of length j. int cutRodRecur(int i, int j, vector<int> &price,                  vector<vector<int>> &memo) {          // base case      if (i==0 || j==0) return 0;          // If value if memoized     if (memo[i][j]!=-1) return memo[i][j];          // There are two options:     // 1. Break it into (i) and (i-j) rods and      // take value of ith rod.          int take = 0;     if (i<=j) {         take = price[i-1] + cutRodRecur(i, j-i, price, memo);     }          // 2. Skip i'th length rod.     int noTake = cutRodRecur(i-1, j, price, memo);          return memo[i][j] = max(take, noTake); }  int cutRod(vector<int> &price) {     int n = price.size();     vector<vector<int>> memo(n+1, vector<int>(n+1, -1));          return cutRodRecur(n, n, price, memo); }  int main() {     vector<int> price =  { 1, 5, 8, 9, 10, 17, 17, 20};     cout << cutRod(price);     return 0; } 
Java
// Java program to find maximum // profit from rod of size n   import java.util.Arrays;  class GfG {      // Find the maximum value obtainable from rod      // of length j.     static int cutRodRecur(int i, int j,                             int[] price, int[][] memo) {          // base case          if (i == 0 || j == 0) return 0;          // If value is memoized         if (memo[i][j] != -1) return memo[i][j];          // There are two options:         // 1. Break it into (i) and (i-j) rods and          // take value of ith rod.         int take = 0;         if (i <= j) {             take = price[i - 1] + cutRodRecur(i, j - i, price, memo);         }          // 2. Skip i'th length rod.         int noTake = cutRodRecur(i - 1, j, price, memo);          return memo[i][j] = Math.max(take, noTake);     }      static int cutRod(int[] price) {         int n = price.length;         int[][] memo = new int[n + 1][n + 1];         for (int[] row : memo) {             Arrays.fill(row, -1);         }          return cutRodRecur(n, n, price, memo);     }      public static void main(String[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         System.out.println(cutRod(price));     } } 
Python
# Python program to find maximum # profit from rod of size n   def cutRodRecur(i, j, price, memo):      # base case      if i == 0 or j == 0:         return 0      # If value is memoized     if memo[i][j] != -1:         return memo[i][j]      # There are two options:     # 1. Break it into (i) and (i-j) rods and      # take value of ith rod.     take = 0     if i <= j:         take = price[i - 1] + cutRodRecur(i, j - i, price, memo)      # 2. Skip i'th length rod.     noTake = cutRodRecur(i - 1, j, price, memo)      memo[i][j] = max(take, noTake)     return memo[i][j]  def cutRod(price):     n = len(price)     memo = [[-1 for _ in range(n + 1)] for _ in range(n + 1)]     return cutRodRecur(n, n, price, memo)  if __name__ == "__main__":     price = [1, 5, 8, 9, 10, 17, 17, 20]     print(cutRod(price)) 
C#
// C# program to find maximum // profit from rod of size n   using System;  class GfG {      // Find the maximum value obtainable from rod      // of length j.     static int cutRodRecur(int i, int j,                             int[] price, int[,] memo) {          // base case          if (i == 0 || j == 0) return 0;          // If value is memoized         if (memo[i, j] != -1) return memo[i, j];          // There are two options:         // 1. Break it into (i) and (i-j) rods and          // take value of ith rod.         int take = 0;         if (i <= j) {             take = price[i - 1] + cutRodRecur(i, j - i, price, memo);         }          // 2. Skip i'th length rod.         int noTake = cutRodRecur(i - 1, j, price, memo);          memo[i, j] = Math.Max(take, noTake);         return memo[i, j];     }      static int cutRod(int[] price) {         int n = price.Length;         int[,] memo = new int[n + 1, n + 1];         for (int i = 0; i <= n; i++) {             for (int j = 0; j <= n; j++) {                 memo[i, j] = -1;             }         }          return cutRodRecur(n, n, price, memo);     }      static void Main(string[] args) {         int[] price = {1, 5, 8, 9, 10, 17, 17, 20};         Console.WriteLine(cutRod(price));     } } 
JavaScript
// JavaScript program to find maximum // profit from rod of size n   function cutRodRecur(i, j, price, memo) {      // base case      if (i === 0 || j === 0) return 0;      // If value is memoized     if (memo[i][j] !== -1) return memo[i][j];      // There are two options:     // 1. Break it into (i) and (i-j) rods and      // take value of ith rod.     let take = 0;     if (i <= j) {         take = price[i - 1] + cutRodRecur(i, j - i, price, memo);     }      // 2. Skip i'th length rod.     const noTake = cutRodRecur(i - 1, j, price, memo);      memo[i][j] = Math.max(take, noTake);     return memo[i][j]; }  function cutRod(price) {     const n = price.length;     const memo = Array.from({ length: n + 1 }, () => Array(n + 1).fill(-1));      return cutRodRecur(n, n, price, memo); }  const price = [1, 5, 8, 9, 10, 17, 17, 20]; console.log(cutRod(price)); 

Output
22

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    Longest Increasing Subsequence (LIS)
    Given an array arr[] of size n, the task is to find the length of the Longest Increasing Subsequence (LIS) i.e., the longest possible subsequence in which the elements of the subsequence are sorted in increasing order.Examples: Input: arr[] = [3, 10, 2, 1, 20]Output: 3Explanation: The longest increa
    14 min read
    Longest subsequence such that difference between adjacents is one
    Given an array arr[] of size n, the task is to find the longest subsequence such that the absolute difference between adjacent elements is 1.Examples: Input: arr[] = [10, 9, 4, 5, 4, 8, 6]Output: 3Explanation: The three possible subsequences of length 3 are [10, 9, 8], [4, 5, 4], and [4, 5, 6], wher
    15+ min read
    Maximum size square sub-matrix with all 1s
    Given a binary matrix mat of size n * m, the task is to find out the maximum length of a side of a square sub-matrix with all 1s.Example:Input: mat = [ [0, 1, 1, 0, 1], [1, 1, 0, 1, 0], [0, 1, 1, 1, 0], [1, 1, 1, 1, 0], [1, 1, 1, 1, 1], [0, 0, 0, 0, 0] ]Output: 3Explanation: The maximum length of a
    15+ min read
    Min Cost Path
    You are given a 2D matrix cost[][] of dimensions m × n, where each cell represents the cost of traversing through that position. Your goal is to determine the minimum cost required to reach the bottom-right cell (m-1, n-1) starting from the top-left cell (0,0).The total cost of a path is the sum of
    15+ min read
    Longest Common Substring (Space optimized DP solution)
    Given two strings ‘s1‘ and ‘s2‘, find the length of the longest common substring. Example: Input: s1 = “GeeksforGeeks”, s2 = “GeeksQuiz” Output : 5 Explanation:The longest common substring is “Geeks” and is of length 5.Input: s1 = “abcdxyz”, s2 = “xyzabcd” Output : 4Explanation:The longest common su
    7 min read
    Count ways to reach the nth stair using step 1, 2 or 3
    A child is running up a staircase with n steps and can hop either 1 step, 2 steps, or 3 steps at a time. The task is to implement a method to count how many possible ways the child can run up the stairs.Examples: Input: 4Output: 7Explanation: There are seven ways: {1, 1, 1, 1}, {1, 2, 1}, {2, 1, 1},
    15+ min read
    Grid Unique Paths - Count Paths in matrix
    Given an matrix of size m x n, the task is to find the count of all unique possible paths from top left to the bottom right with the constraints that from each cell we can either move only to the right or down.Examples: Input: m = 2, n = 2Output: 2Explanation: There are two paths(0, 0) -> (0, 1)
    15+ min read
    Unique paths in a Grid with Obstacles
    Given a matrix mat[][] of size n * m, where mat[i][j] = 1 indicates an obstacle and mat[i][j] = 0 indicates an empty space. The task is to find the number of unique paths to reach (n-1, m-1) starting from (0, 0). You are allowed to move in the right or downward direction. Note: In the grid, cells ma
    15+ min read

    Medium problems on Dynamic programming

    0/1 Knapsack Problem
    Given n items where each item has some weight and profit associated with it and also given a bag with capacity W, [i.e., the bag can hold at most W weight in it]. The task is to put the items into the bag such that the sum of profits associated with them is the maximum possible. Note: The constraint
    15+ min read
    Printing Items in 0/1 Knapsack
    Given weights and values of n items, put these items in a knapsack of capacity W to get the maximum total value in the knapsack. In other words, given two integer arrays, val[0..n-1] and wt[0..n-1] represent values and weights associated with n items respectively. Also given an integer W which repre
    12 min read
    Unbounded Knapsack (Repetition of items allowed)
    Given a knapsack weight, say capacity and a set of n items with certain value vali and weight wti, The task is to fill the knapsack in such a way that we can get the maximum profit. This is different from the classical Knapsack problem, here we are allowed to use an unlimited number of instances of
    15+ min read
    Egg Dropping Puzzle | DP-11
    You are given n identical eggs and you have access to a k-floored building from 1 to k.There exists a floor f where 0 <= f <= k such that any egg dropped from a floor higher than f will break, and any egg dropped from or below floor f will not break. There are a few rules given below:An egg th
    15+ min read
    Word Break
    Given a string s and y a dictionary of n words dictionary, check if s can be segmented into a sequence of valid words from the dictionary, separated by spaces.Examples:Input: s = "ilike", dictionary[] = ["i", "like", "gfg"]Output: trueExplanation: The string can be segmented as "i like".Input: s = "
    12 min read
    Vertex Cover Problem (Dynamic Programming Solution for Tree)
    A vertex cover of an undirected graph is a subset of its vertices such that for every edge (u, v) of the graph, either ‘u’ or ‘v’ is in vertex cover. Although the name is Vertex Cover, the set covers all edges of the given graph. The problem to find minimum size vertex cover of a graph is NP complet
    15+ min read
    Tile Stacking Problem
    Given integers n (the height of the tower), m (the maximum size of tiles available), and k (the maximum number of times each tile size can be used), the task is to calculate the number of distinct stable towers of height n that can be built. Note:A stable tower consists of exactly n tiles, each stac
    15+ min read
    Box Stacking Problem
    Given three arrays height[], width[], and length[] of size n, where height[i], width[i], and length[i] represent the dimensions of a box. The task is to create a stack of boxes that is as tall as possible, but we can only stack a box on top of another box if the dimensions of the 2-D base of the low
    15+ min read
    Partition a Set into Two Subsets of Equal Sum
    Given an array arr[], the task is to check if it can be partitioned into two parts such that the sum of elements in both parts is the same.Note: Each element is present in either the first subset or the second subset, but not in both.Examples: Input: arr[] = [1, 5, 11, 5]Output: true Explanation: Th
    15+ min read
    Travelling Salesman Problem using Dynamic Programming
    Given a 2d matrix cost[][] of size n where cost[i][j] denotes the cost of moving from city i to city j. The task is to complete a tour from city 0 (0-based index) to all other cities such that we visit each city exactly once and then at the end come back to city 0 at minimum cost.Note the difference
    15 min read
    Longest Palindromic Subsequence (LPS)
    Given a string s, find the length of the Longest Palindromic Subsequence in it. Note: The Longest Palindromic Subsequence (LPS) is the maximum-length subsequence of a given string that is also a Palindrome. Longest Palindromic SubsequenceExamples:Input: s = "bbabcbcab"Output: 7Explanation: Subsequen
    15+ min read
    Longest Common Increasing Subsequence (LCS + LIS)
    Given two arrays, a[] and b[], find the length of the longest common increasing subsequence(LCIS). LCIS refers to a subsequence that is present in both arrays and strictly increases.Prerequisites: LCS, LIS.Examples:Input: a[] = [3, 4, 9, 1], b[] = [5, 3, 8, 9, 10, 2, 1]Output: 2Explanation: The long
    15+ min read
    Find all distinct subset (or subsequence) sums of an array
    Given an array arr[] of size n, the task is to find a distinct sum that can be generated from the subsets of the given sets and return them in increasing order. It is given that the sum of array elements is small.Examples: Input: arr[] = [1, 2]Output: [0, 1, 2, 3]Explanation: Four distinct sums can
    15+ min read
    Weighted Job Scheduling
    Given a 2D array jobs[][] of order n*3, where each element jobs[i] defines start time, end time, and the profit associated with the job. The task is to find the maximum profit you can take such that there are no two jobs with overlapping time ranges.Note: If the job ends at time X, it is allowed to
    15+ min read
    Count Derangements (Permutation such that no element appears in its original position)
    A Derangement is a permutation of n elements, such that no element appears in its original position. For example, a derangement of [0, 1, 2, 3] is [2, 3, 1, 0].Given a number n, find the total number of Derangements of a set of n elements.Examples : Input: n = 2Output: 1Explanation: For two balls [1
    12 min read
    Minimum insertions to form a palindrome
    Given a string s, the task is to find the minimum number of characters to be inserted to convert it to a palindrome.Examples:Input: s = "geeks"Output: 3Explanation: "skgeegks" is a palindromic string, which requires 3 insertions.Input: s= "abcd"Output: 3Explanation: "abcdcba" is a palindromic string
    15+ min read
    Ways to arrange Balls such that adjacent balls are of different types
    There are 'p' balls of type P, 'q' balls of type Q and 'r' balls of type R. Using the balls we want to create a straight line such that no two balls of the same type are adjacent.Examples : Input: p = 1, q = 1, r = 0Output: 2Explanation: There are only two arrangements PQ and QPInput: p = 1, q = 1,
    15+ min read
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