Maximum path sum in a triangle. (original) (raw)
Last Updated : 23 Jul, 2025
We have given numbers in form of a triangle, by starting at the top of the triangle and moving to adjacent numbers on the row below, find the maximum total from top to bottom.
Examples :
Input : 3 7 4 2 4 6 8 5 9 3 Output : 23 Explanation : 3 + 7 + 4 + 9 = 23
Input : 8 -4 4 2 2 6 1 1 1 1 Output : 19 Explanation : 8 + 4 + 6 + 1 = 19
Method 1: We can go through the brute force by checking every possible path but that is much time taking so we should try to solve this problem with the help of dynamic programming which reduces the time complexity.
Implementation of Recursive Approach:
C++ `
// C++ program for // Recursive implementation of // Max sum problem in a triangle #include<bits/stdc++.h> using namespace std; #define N 3
// Function for finding maximum sum int maxPathSum(int tri[][N], int i, int j, int row, int col){ if(j == col ){ return 0; }
if(i == row-1 ){
return tri[i][j] ;
}
return tri[i][j] + max(maxPathSum(tri, i+1, j, row, col),
maxPathSum(tri, i+1, j+1, row, col)) ;}
/* Driver program to test above functions */ int main() { int tri[N][N] = { {1, 0, 0}, {4, 8, 0}, {1, 5, 3} }; cout << maxPathSum(tri, 0, 0, 3, 3); return 0; }
Java
// Java program for // Recursive implementation of // Max sum problem in a triangle import java.io.*;
class GFG { static int N = 3;
// Function for finding maximum sum
public static int maxPathSum(int tri[][], int i, int j,
int row, int col)
{
if (j == col) {
return 0;
}
if (i == row - 1) {
return tri[i][j];
}
return tri[i][j]
+ Math.max(
maxPathSum(tri, i + 1, j, row, col),
maxPathSum(tri, i + 1, j + 1, row, col));
}
/* Driver program to test above functions */
public static void main(String[] args)
{
int tri[][]
= { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } };
System.out.print(maxPathSum(tri, 0, 0, 3, 3));
}}
// This code is contributed by Rohit Pradhan
Python3
Python program for
Recursive implementation of
Max sum problem in a triangle
N = 3
Function for finding maximum sum
def maxPathSum(tri, i, j, row, col): if(j == col ): return 0
if(i == row-1 ):
return tri[i][j]
return tri[i][j] + max(maxPathSum(tri, i+1, j, row, col),
maxPathSum(tri, i+1, j+1, row, col))Driver program to test above functions
tri = [ [1, 0, 0],[4, 8, 0],[1, 5, 3] ] print(maxPathSum(tri, 0, 0, 3, 3))
This code is contributed by shinjanpatra
C#
// C# program for Recursive implementation // of Max sum problem in a triangle using System;
public class GFG { static int N = 3;
public static int max(int a, int b){ if(a > b) return a; return b; }
// Function for finding maximum sum public static int maxPathSum(int[,] tri, int i, int j, int row, int col) { if (j == col) { return 0; }
if (i == row - 1) {
return tri[i,j];
}
return tri[i,j]
+ max(
maxPathSum(tri, i + 1, j, row, col),
maxPathSum(tri, i + 1, j + 1, row, col)
);}
// Driver program to test above functions public static void Main(string[] args) { int[,] tri = {{ 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; Console.WriteLine(maxPathSum(tri, 0, 0, 3, 3)); } }
// This code is contributed by ajaymakavana.
JavaScript
`
Complexity Analysis:
- Time Complexity: O(2N*N)
- Auxiliary Space: O(N)
If we should left shift every element and put 0 at each empty position to make it a regular matrix, then our problem looks like minimum cost path.
So, after converting our input triangle elements into a regular matrix we should apply the dynamic programming concept to find the maximum path sum.
Method 2: DP Top-Down
Since there are overlapping subproblems, we can avoid the repeated work done in method 1 by storing the min-cost path calculated so far using top-down approach
C++ `
// C++ program for Dynamic // Programming implementation (Top-Down) of // Max sum problem in a triangle #include<bits/stdc++.h> using namespace std; #define N 3
// Function for finding maximum sum int maxPathSum(int tri[][N], int i, int j, int row, int col, vector<vector> &dp){ if(j == col ){ return 0; }
if(i == row-1 ){
return tri[i][j] ;
}
if(dp[i][j] != -1){
return dp[i][j] ;
}
return dp[i][j] = tri[i][j] + max(maxPathSum(tri, i+1, j, row, col, dp),
maxPathSum(tri, i+1, j+1, row, col, dp)) ;}
/* Driver program to test above functions */ int main() { int tri[N][N] = { {1, 0, 0}, {4, 8, 0}, {1, 5, 3} }; vector<vector> dp(N, vector(N, -1) ) ; cout << maxPathSum(tri, 0, 0, N, N, dp); return 0; }
Java
// Java program for Dynamic // Programming implementation (Top-Down) of // Max sum problem in a triangle
import java.io.; import java.util.;
class GFG {
// Function for finding maximum sum static int maxPathSum(int[][] tri, int i, int j, int row, int col, int[][] dp) { if (j == col) { return 0; }
if (i == row - 1) {
return tri[i][j];
}
if (dp[i][j] != -1) {
return dp[i][j];
}
return dp[i][j]
= tri[i][j]
+ Math.max(
maxPathSum(tri, i + 1, j, row, col, dp),
maxPathSum(tri, i + 1, j + 1, row, col,
dp));}
public static void main(String[] args) { int n = 3; int[][] tri = { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; int[][] dp = new int[n][n]; for (int[] row : dp) { Arrays.fill(row, -1); } System.out.print(maxPathSum(tri, 0, 0, n, n, dp)); } }
// This code is contributed by lokeshmvs21.
Python3
C++ program for Dynamic
Programming implementation (Top-Down) of
Max sum problem in a triangle
N = 3
Function for finding maximum sum
def maxPathSum(tri, i, j, row, col, dp): if(j == col): return 0
if(i == row-1):
return tri[i][j]
if(dp[i][j] != -1):
return -1
dp[i][j] = tri[i][j] + max(maxPathSum(tri, i+1, j, row, col, dp),
maxPathSum(tri, i+1, j+1, row, col, dp))
return dp[i][j]Driver program to test above functions
tri = [ [1, 0, 0], [4, 8, 0], [1, 5, 3] ] dp = [[-1 for i in range(N)]for j in range(N)] print(maxPathSum(tri, 0, 0, N, N, dp))
This code is contributed by shinjanpatra
C#
// C# program for Dynamic // Programming implementation (Top-Down) of // Max sum problem in a triangle using System; class GFG {
// Function for finding maximum sum static int maxPathSum(int[, ] tri, int i, int j, int row, int col, int[, ] dp) { if (j == col) { return 0; }
if (i == row - 1) {
return tri[i, j];
}
if (dp[i, j] != -1) {
return dp[i, j];
}
return dp[i, j]
= tri[i, j]
+ Math.Max(
maxPathSum(tri, i + 1, j, row, col, dp),
maxPathSum(tri, i + 1, j + 1, row, col,
dp));} static void Main() { int[, ] tri = { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; int N = 3; int[, ] dp = new int[N, N]; for (int i = 0; i < N; i++) for (int j = 0; j < N; j++) dp[i, j] = -1; Console.Write(maxPathSum(tri, 0, 0, N, N, dp)); } }
// This code is contributed by garg28harsh.
JavaScript
`
Complexity Analysis:
- Time Complexity: O(m*n) where m = no of rows and n = no of columns
- Auxiliary Space: O(n2)
Method 3: DP(Bottom - UP)
Since there are overlapping subproblems, we can avoid the repeated work done in method 1 by storing the min-cost path calculated so far using the bottom-up approach thus reducing stack space
C++ `
// C++ program for Dynamic // Programming implementation of // Max sum problem in a triangle #include<bits/stdc++.h> using namespace std; #define N 3
// Function for finding maximum sum int maxPathSum(int tri[][N], int n, vector<vector> &dp) { // loop for bottom-up calculation for(int j = 0; j < n; j++ ){ dp[n-1][j] = tri[n-1][j] ; }
for(int i = n-2; i >= 0; i--){
for(int j = i; j >= 0; j-- ){
dp[i][j] = tri[i][j] + max(dp[i+1][j] , dp[i+1][j+1]) ;
}
}
return dp[0][0] ;
}
/* Driver program to test above functions */ int main() { int tri[N][N] = { {1, 0, 0}, {4, 8, 0}, {1, 5, 3} }; vector<vector> dp(N, vector(N, -1) ) ; cout << maxPathSum(tri, N, dp); return 0; }
Java
// Java program for Dynamic // Programming implementation of // Max sum problem in a triangle public class Main {
// Function for finding maximum sum static int maxPathSum(int[][] tri, int n, int[][] dp) {
// loop for bottom-up calculation
for (int j = 0; j < n; j++) {
dp[n - 1][j] = tri[n - 1][j];
}
for (int i = n - 2; i >= 0; i--) {
for (int j = i; j >= 0; j--) {
dp[i][j] = tri[i][j]
+ Math.max(dp[i + 1][j],
dp[i + 1][j + 1]);
}
}
return dp[0][0];}
public static void main(String[] args) { int N = 3; int[][] tri = { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; int[][] dp = new int[N][N]; for (int i = 0; i < N; i++) { for (int j = 0; j < N; j++) { dp[i][j] = -1; } }
System.out.println(maxPathSum(tri, N, dp));} }
// This code is contributed by garg28harsh.
Python3
Python program for Dynamic
Programming implementation of
Max sum problem in a triangle
Number of rows in the triangle
N = 3
Function for finding maximum sum
def maxPathSum(tri, n, dp): # Loop for bottom-up calculation for j in range(n): dp[n-1][j] = tri[n-1][j]
for i in range(n-2, -1, -1):
for j in range(i, -1, -1):
dp[i][j] = tri[i][j] + max(dp[i+1][j], dp[i+1][j+1])
# Return the maximum sum
return dp[0][0]Driver program to test above functions
if name == 'main': # Triangle of numbers tri = [[1, 0, 0], [4, 8, 0], [1, 5, 3]]
# Initialize dp array with -1
dp = [[-1 for j in range(N)] for i in range(N)]
# Print the maximum sum
print(maxPathSum(tri, N, dp))This code is contributed by divyansh2212
C#
// C# program for Dynamic // Programming implementation of // Max sum problem in a triangle
using System;
public class GFG {
// Function for finding maximum sum
static int maxPathSum(int[, ] tri, int n, int[, ] dp)
{
// loop for bottom-up calculation
for (int j = 0; j < n; j++) {
dp[n - 1, j] = tri[n - 1, j];
}
for (int i = n - 2; i >= 0; i--) {
for (int j = i; j >= 0; j--) {
dp[i, j] = tri[i, j]
+ Math.Max(dp[i + 1, j],
dp[i + 1, j + 1]);
}
}
return dp[0, 0];
}
public static void Main(string[] args)
{
int N = 3;
int[, ] tri = new int[, ] { { 1, 0, 0 },
{ 4, 8, 0 },
{ 1, 5, 3 } };
int[, ] dp = new int[N, N];
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
dp[i, j] = -1;
}
}
Console.WriteLine(maxPathSum(tri, N, dp));
}} // This code is contributed by karandeep1234
JavaScript
// Javascript program for Dynamic // Programming implementation of // Max sum problem in a triangle let N = 3
// Function for finding maximum sum function maxPathSum(tri, n, dp) { // loop for bottom-up calculation for(let j = 0; j < n; j++ ){ dp[n-1][j] = tri[n-1][j] ; }
for(let i = n-2; i >= 0; i--){
for(let j = i; j >= 0; j-- ){
dp[i][j] = tri[i][j] + Math.max(dp[i+1][j] , dp[i+1][j+1]) ;
}
}
return dp[0][0] ;
}
/* Driver program to test above functions */ let tri = [ [1, 0, 0], [4, 8, 0], [1, 5, 3] ]; let dp = new Array(N); for(let i = 0; i < N; i++) dp[i] = new Array(N).fill(-1); console.log(maxPathSum(tri, N, dp));
// This code is contributed by poojaagarwal2.
`
Complexity Analysis:
- Time Complexity: O(m*n) where m = no of rows and n = no of columns
- Auxiliary Space: O(n2)
Method 4: Space Optimization (Without Changning input matrix)
We do not need a 2d matrix we only need a 1d array that stores the minimum of the immediate next column and thus we can reduce space
C++ `
// C++ program for Dynamic // Programming implementation of // Max sum problem in a triangle #include<bits/stdc++.h> using namespace std; #define N 3
// Function for finding maximum sum int maxPathSum(int tri[][N], int n, vector<vector> &dp) { vector front(n, -1) , curr(n, -1) ;
for(int j = 0; j < n; j++ ){
front[j] = tri[n-1][j] ;
}
for(int i = n-2; i >= 0; i--){
for(int j = i; j >= 0; j-- ){
curr[j] = tri[i][j] + max(front[j] , front[j+1]) ;
}
front = curr ;
}
return front[0] ;
}
/* Driver program to test above functions */ int main() { int tri[N][N] = { {1, 0, 0}, {4, 8, 0}, {1, 5, 3} }; vector<vector> dp(N, vector(N, -1) ) ; cout << maxPathSum(tri, N, dp); return 0; }
Java
// Java program for Dynamic // Programming implementation of // Max sum problem in a triangle public class GFG {
// Function for finding maximum sum static int maxPathSum(int[][] tri, int n, int[][] dp) {
int front[] = new int[n];
int curr[] = new int[n];
for (int j = 0; j < n; j++) {
front[j] = tri[n - 1][j];
curr[j] = -1;
}
for (int i = n - 2; i >= 0; i--) {
for (int j = i; j >= 0; j--) {
curr[j]
= tri[i][j]
+ Math.max(front[j], front[j + 1]);
}
front = curr;
}
return front[0];} public static void main(String[] args) { int N = 3; int[][] tri = { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; int[][] dp = new int[N][N]; for (int i = 0; i < N; i++) { for (int j = 0; j < N; j++) { dp[i][j] = -1; } }
System.out.println(maxPathSum(tri, N, dp));} }
// This code is contributed by garg28harsh.
Python3
Python program for Dynamic
Programming implementation of
Max sum problem in a triangle
N=3
Function for finding maximum sum
def maxPathSum(tri,n,dp): front=[-1]*n curr=[-1]*n for j in range(n): front[j] = tri[n-1][j]
for i in range(n-2,-1,-1):
for j in range(i,-1,-1):
curr[j] = tri[i][j] + max(front[j] ,front[j+1])
front=curr
return front[0]Driver program to test above functions
tri=[[1, 0, 0],[4,8,0],[1,5,3]] dp= [[-1 for i in range(N)] for j in range(N)] print(maxPathSum(tri,N,dp))
This code is contributed by Pushpesh Raj.
C#
// C# program for Dynamic // Programming implementation of // Max sum problem in a triangle using System; public class GFG {
// Function for finding maximum sum static int maxPathSum(int[, ] tri, int n, int[, ] dp) {
int[] front = new int[n];
int[] curr = new int[n];
for (int j = 0; j < n; j++) {
front[j] = tri[n - 1, j];
curr[j] = -1;
}
for (int i = n - 2; i >= 0; i--) {
for (int j = i; j >= 0; j--) {
curr[j]
= tri[i, j]
+ Math.Max(front[j], front[j + 1]);
}
front = curr;
}
return front[0];} public static void Main(string[] args) { int N = 3; int[, ] tri = { { 1, 0, 0 }, { 4, 8, 0 }, { 1, 5, 3 } }; int[, ] dp = new int[N, N]; for (int i = 0; i < N; i++) { for (int j = 0; j < N; j++) { dp[i, j] = -1; } }
Console.WriteLine(maxPathSum(tri, N, dp));} }
// This code is contributed by karandeep1234
JavaScript
// Javascript program for Dynamic // Programming implementation of // Max sum problem in a triangle let N = 3
// Function for finding maximum sum function maxPathSum(tri, n, dp) { let front= new Array(n).fill(-1); let curr=new Array(n).fill(-1);
for(let j = 0; j < n; j++ ){
front[j] = tri[n-1][j] ;
}
for(let i = n-2; i >= 0; i--){
for(let j = i; j >= 0; j-- ){
curr[j] = tri[i][j] + Math.max(front[j] , front[j+1]) ;
}
front = curr ;
}
return front[0] ;
}
/* Driver program to test above functions */ let tri = [ [1, 0, 0],[4, 8, 0],[1, 5, 3]]; dp = new Array(N); for(let i = 0; i < N; i++) dp[i] = new Array(N).fill(-1); console.log(maxPathSum(tri, N, dp));
// This code is contributed by ritaagarwal.
`
Complexity Analysis:
- Time Complexity: O(m*n) where m = no of rows and n = no of columns
- Auxiliary Space: O(n)
Method 5: Space Optimization (Changing input matrix)
Applying, DP in bottom-up manner we should solve our problem as:
Example:
3 7 4 2 4 6 8 5 9 3
Step 1 : 3 0 0 0 7 4 0 0 2 4 6 0 8 5 9 3
Step 2 : 3 0 0 0 7 4 0 0 10 13 15 0
Step 3 : 3 0 0 0 20 19 0 0
Step 4: 23 0 0 0
output : 23
C++ `
// C++ program for Dynamic // Programming implementation of // Max sum problem in a triangle #include<bits/stdc++.h> using namespace std; #define N 3
// Function for finding maximum sum int maxPathSum(int tri[][N], int m, int n) { // loop for bottom-up calculation for (int i=m-1; i>=0; i--) { for (int j=0; j<=i; j++) { // for each element, check both // elements just below the number // and below right to the number // add the maximum of them to it if (tri[i+1][j] > tri[i+1][j+1]) tri[i][j] += tri[i+1][j]; else tri[i][j] += tri[i+1][j+1]; } }
// return the top element
// which stores the maximum sum
return tri[0][0];}
/* Driver program to test above functions */ int main() { int tri[N][N] = { {1, 0, 0}, {4, 8, 0}, {1, 5, 3} }; cout << maxPathSum(tri, 2, 2); return 0; }
Java
// Java Program for Dynamic // Programming implementation of // Max sum problem in a triangle import java.io.*;
class GFG {
static int N = 3;
// Function for finding maximum sum
static int maxPathSum(int tri[][], int m, int n)
{
// loop for bottom-up calculation
for (int i = m - 1; i >= 0; i--)
{
for (int j = 0; j <= i; j++)
{
// for each element, check both
// elements just below the number
// and below right to the number
// add the maximum of them to it
if (tri[i + 1][j] > tri[i + 1][j + 1])
tri[i][j] += tri[i + 1][j];
else
tri[i][j] += tri[i + 1][j + 1];
}
}
// return the top element
// which stores the maximum sum
return tri[0][0];
}
/* Driver program to test above functions */
public static void main (String[] args)
{
int tri[][] = { {1, 0, 0},
{4, 8, 0},
{1, 5, 3} };
System.out.println ( maxPathSum(tri, 2, 2));
}}
// This code is contributed by vt_m
Python3
Python program for
Dynamic Programming
implementation of Max
sum problem in a
triangle
N = 3
Function for finding maximum sum
def maxPathSum(tri, m, n):
# loop for bottom-up calculation
for i in range(m-1, -1, -1):
for j in range(i+1):
# for each element, check both
# elements just below the number
# and below right to the number
# add the maximum of them to it
if (tri[i+1][j] > tri[i+1][j+1]):
tri[i][j] += tri[i+1][j]
else:
tri[i][j] += tri[i+1][j+1]
# return the top element
# which stores the maximum sum
return tri[0][0]Driver program to test above function
tri = [[1, 0, 0], [4, 8, 0], [1, 5, 3]] print(maxPathSum(tri, 2, 2))
This code is contributed
by Soumen Ghosh.
C#
// C# Program for Dynamic Programming // implementation of Max sum problem // in a triangle using System;
class GFG {
// Function for finding maximum sum
static int maxPathSum(int [,]tri,
int m, int n)
{
// loop for bottom-up calculation
for (int i = m - 1; i >= 0; i--)
{
for (int j = 0; j <= i; j++)
{
// for each element,
// check both elements
// just below the number
// and below right to
// the number add the
// maximum of them to it
if (tri[i + 1,j] >
tri[i + 1,j + 1])
tri[i,j] +=
tri[i + 1,j];
else
tri[i,j] +=
tri[i + 1,j + 1];
}
}
// return the top element
// which stores the maximum sum
return tri[0,0];
}
/* Driver program to test above
functions */
public static void Main ()
{
int [,]tri = { {1, 0, 0},
{4, 8, 0},
{1, 5, 3} };
Console.Write (
maxPathSum(tri, 2, 2));
}}
// This code is contributed by nitin mittal.
PHP
JavaScript
`
Complexity Analysis:
- Time Complexity: O(m*n) where m = no of rows and n = no of columns
- Auxiliary Space: O(1)