Given are N boards of with length of each given in the form of array, and K painters, such that each painter takes 1 unit of time to paint 1 unit of the board. The task is to find the minimum time to paint all boards under the constraints that any painter will only paint continuous sections of boards, say board {2, 3, 4} or only board {1} or nothing but not board {2, 4, 5}.
Examples:
Input: N = 4, A = {10, 10, 10, 10}, K = 2
Output : 20
Explanation: Here we can divide the boards into 2 equal sized partitions (Painter 1 will paint boards A1 and A2, and Painter 2 will paint boards A3 and A4). So each painter gets 20 units of board and the total time taken is 20.
Input: N = 4, A = {10, 20, 30, 40}, K = 2
Output : 60
Explanation: Since there are only 2 painters, therefore divide first 3 boards to painter 1 (A1, A2 and A3) with time = 60, and last board to painter 2 (A4) with time = 40. Therefore total time taken = 60, which is the minimum possible.
Please note the combination A1 and A4 to Painter 1 with time 50, and A2 and A3 to Painter 2 with time 50, will yield a smaller time (50 units). But this cant be considered due to the constraint that a painter cannot paint non-continuos series of boards.
Naive Approach for Painter’s Problem:
A brute force solution is to consider all possible sets of contiguous partitions and calculate the maximum sum partition in each case and return the minimum of all these cases.
Dynamic Programming Approach for Painter’s Problem
The above approach can be further optimised using Dynamic Programming approach.
From the above examples, it is obvious that the strategy of dividing the boards into k equal partitions won’t work for all cases. We can observe that the problem can be broken down into: Given an array A of non-negative integers and a positive integer k, we have to divide A into k of fewer partitions such that the maximum sum of the elements in a partition, overall partitions is minimized. So for the second example above, possible divisions are:
- One partition: so time is 100.
-
Two partitions: (10) & (20, 30, 40), so time is 90. Similarly, we can put the first divider
after 20 (=> time 70) or 30 (=> time 60); so this means the minimum time: (100, 90, 70, 60) is 60.
Optimal Substructure Approach for Painter’s Problem using DP
We can implement the naive solution using recursion with the following optimal substructure property:
- Assuming that we already have k-1 partitions in place (using k-2 dividers), we now have to put the k-1 th divider to get k partitions.
- We can put the k-1 th divider between the i th and i+1 th element where i = 1 to n.
- Please note that putting it before the first element is the same as putting it after the last element.
- The total cost of this arrangement can be calculated as the maximum of the following:
- The cost of the last partition: sum(Ai…..An), where the k-1 th divider is before element i.
- This can be found out using a simple helper function to calculate sum of elements between two indices in the array.
- The maximum cost of any partition already formed to the left of the k-1 th divider.
- We can observe that this is actually to place the k-2 separators as fairly as possible, so it is a subproblem of the given problem.
- Thus we can write the optimal substructure property as the following recurrence relation:
Following is the implementation of the above recursive equation:
// CPP program for The painter's partition problem #include <climits> #include <iostream> using namespace std;
// function to calculate sum between two indices // in array int sum( int arr[], int from, int to)
{ int total = 0;
for ( int i = from; i <= to; i++)
total += arr[i];
return total;
} // for n boards and k partitions int partition( int arr[], int n, int k)
{ // base cases
if (k == 1) // one partition
return sum(arr, 0, n - 1);
if (n == 1) // one board
return arr[0];
int best = INT_MAX;
// find minimum of all possible maximum
// k-1 partitions to the left of arr[i],
// with i elements, put k-1 th divider
// between arr[i-1] & arr[i] to get k-th
// partition
for ( int i = 1; i <= n; i++)
best = min(best, max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
return best;
} int main()
{ int arr[] = { 10, 20, 60, 50, 30, 40 };
int n = sizeof (arr) / sizeof (arr[0]);
int k = 3;
cout << partition(arr, n, k) << endl;
return 0;
} |
// Java Program for The painter's partition problem import java.io.*;
import java.util.*;
class GFG {
// function to calculate sum between two indices
// in array
static int sum( int arr[], int from, int to)
{
int total = 0 ;
for ( int i = from; i <= to; i++)
total += arr[i];
return total;
}
// for n boards and k partitions
static int partition( int arr[], int n, int k)
{
// base cases
if (k == 1 ) // one partition
return sum(arr, 0 , n - 1 );
if (n == 1 ) // one board
return arr[ 0 ];
int best = Integer.MAX_VALUE;
// find minimum of all possible maximum
// k-1 partitions to the left of arr[i],
// with i elements, put k-1 th divider
// between arr[i-1] & arr[i] to get k-th
// partition
for ( int i = 1 ; i <= n; i++)
best = Math.min(
best, Math.max(partition(arr, i, k - 1 ),
sum(arr, i, n - 1 )));
return best;
}
// Driver code
public static void main(String args[])
{
int arr[] = { 10 , 20 , 60 , 50 , 30 , 40 };
// Calculate size of array.
int n = arr.length;
int k = 3 ;
System.out.println(partition(arr, n, k));
}
} // This code is contributed by Sahil_Bansall |
# Python program for The painter's # partition problem function to # calculate sum between two indices # in array def sum (arr, frm, to):
total = 0
for i in range (frm, to + 1 ):
total + = arr[i]
return total
# for n boards and k partitions def partition(arr, n, k):
# base cases
if k = = 1 : # one partition
return sum (arr, 0 , n - 1 )
if n = = 1 : # one board
return arr[ 0 ]
best = 100000000
# find minimum of all possible
# maximum k-1 partitions to
# the left of arr[i], with i
# elements, put k-1 th divider
# between arr[i-1] & arr[i] to
# get k-th partition
for i in range ( 1 , n + 1 ):
best = min (best,
max (partition(arr, i, k - 1 ),
sum (arr, i, n - 1 )))
return best
# Driver Code arr = [ 10 , 20 , 60 , 50 , 30 , 40 ]
n = len (arr)
k = 3
print (partition(arr, n, k))
# This code is contributed # by sahilshelangia |
// C# Program for The painter's partition problem using System;
class GFG {
// function to calculate sum
// between two indices in array
static int sum( int [] arr, int from , int to)
{
int total = 0;
for ( int i = from ; i <= to; i++)
total += arr[i];
return total;
}
// for n boards and k partitions
static int partition( int [] arr, int n, int k)
{
// base cases
if (k == 1) // one partition
return sum(arr, 0, n - 1);
if (n == 1) // one board
return arr[0];
int best = int .MaxValue;
// find minimum of all possible maximum
// k-1 partitions to the left of arr[i],
// with i elements, put k-1 th divider
// between arr[i-1] & arr[i] to get k-th
// partition
for ( int i = 1; i <= n; i++)
best = Math.Min(
best, Math.Max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
return best;
}
// Driver code
public static void Main()
{
int [] arr = { 10, 20, 60, 50, 30, 40 };
// Calculate size of array.
int n = arr.Length;
int k = 3;
// Function calling
Console.WriteLine(partition(arr, n, k));
}
} // This code is contributed by vt_m |
<?php // PHP program for The // painter's partition problem // function to calculate sum // between two indices in array function sum( $arr , $from , $to )
{ $total = 0;
for ( $i = $from ; $i <= $to ; $i ++)
$total += $arr [ $i ];
return $total ;
} // for n boards // and k partitions function partition( $arr , $n , $k )
{ // base cases
if ( $k == 1) // one partition
return sum( $arr , 0, $n - 1);
if ( $n == 1) // one board
return $arr [0];
$best = PHP_INT_MAX;
// find minimum of all possible
// maximum k-1 partitions to the
// left of arr[i], with i elements,
// put k-1 th divider between
// arr[i-1] & arr[i] to get k-th
// partition
for ( $i = 1; $i <= $n ; $i ++)
$best = min( $best ,
max(partition( $arr , $i , $k - 1),
sum( $arr , $i , $n - 1)));
return $best ;
} // Driver Code $arr = array (10, 20, 60,
50, 30, 40);
$n = sizeof( $arr );
$k = 3;
echo partition( $arr , $n , $k ), "\n" ;
// This code is contributed by ajit ?> |
<script> // JavaScript Program for The painter's // partition problem // Function to calculate sum between // two indices in array function sum(arr, from, to)
{ let total = 0;
for (let i = from; i <= to; i++)
total += arr[i];
return total;
} // For n boards and k partitions function partition(arr, n, k)
{ // Base cases
if (k == 1) // one partition
return sum(arr, 0, n - 1);
if (n == 1) // one board
return arr[0];
let best = Number.MAX_VALUE;
// Find minimum of all possible maximum
// k-1 partitions to the left of arr[i],
// with i elements, put k-1 th divider
// between arr[i-1] & arr[i] to get k-th
// partition
for (let i = 1; i <= n; i++)
best = Math.min(best,
Math.max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
return best;
} // Driver Code let arr = [ 10, 20, 60, 50, 30, 40 ]; // Calculate size of array. let n = arr.length; let k = 3; document.write(partition(arr, n, k)); // This code is contributed by susmitakundugoaldanga </script> |
90
Time complexity: The time complexity of the above solution is exponential.
Auxiliary Space: O(1)
Overlapping sub-problems Approach for Painter’s Problem using DP
Following is the partial recursion tree for T(4, 3) in the above equation.
T(4, 3) / / \ .. T(1, 2) T(2, 2) T(3, 2) /.. /.. T(1, 1) T(1, 1)
We can observe that many subproblems like T(1, 1) in the above problem are being solved again and again. Because of these two properties of this problem, we can solve it using dynamic programming, either by top-down memoized method or bottom-up tabular method.
Following is the implementation of Bottom-Up Tabular approach for Painter’s Problem using DP:
// A DP based CPP program for painter's partition problem #include <climits> #include <iostream> using namespace std;
// function to calculate sum between two indices // in array int sum( int arr[], int from, int to)
{ int total = 0;
for ( int i = from; i <= to; i++)
total += arr[i];
return total;
} // bottom up tabular dp int findMax( int arr[], int n, int k)
{ // initialize table
int dp[k + 1][n + 1] = { 0 };
// base cases
// k=1
for ( int i = 1; i <= n; i++)
dp[1][i] = sum(arr, 0, i - 1);
// n=1
for ( int i = 1; i <= k; i++)
dp[i][1] = arr[0];
// 2 to k partitions
for ( int i = 2; i <= k; i++) { // 2 to n boards
for ( int j = 2; j <= n; j++) {
// track minimum
int best = INT_MAX;
// i-1 th separator before position arr[p=1..j]
for ( int p = 1; p <= j; p++)
best = min(best, max(dp[i - 1][p],
sum(arr, p, j - 1)));
dp[i][j] = best;
}
}
// required
return dp[k][n];
} // driver function int main()
{ int arr[] = { 10, 20, 60, 50, 30, 40 };
int n = sizeof (arr) / sizeof (arr[0]);
int k = 3;
cout << findMax(arr, n, k) << endl;
return 0;
} |
// A DP based Java program for // painter's partition problem import java.io.*;
import java.util.*;
class GFG {
// function to calculate sum between two indices
// in array
static int sum( int arr[], int from, int to)
{
int total = 0 ;
for ( int i = from; i <= to; i++)
total += arr[i];
return total;
}
// bottom up tabular dp
static int findMax( int arr[], int n, int k)
{
// initialize table
int dp[][] = new int [k + 1 ][n + 1 ];
// base cases
// k=1
for ( int i = 1 ; i <= n; i++)
dp[ 1 ][i] = sum(arr, 0 , i - 1 );
// n=1
for ( int i = 1 ; i <= k; i++)
dp[i][ 1 ] = arr[ 0 ];
// 2 to k partitions
for ( int i = 2 ; i <= k; i++) { // 2 to n boards
for ( int j = 2 ; j <= n; j++) {
// track minimum
int best = Integer.MAX_VALUE;
// i-1 th separator before position
// arr[p=1..j]
for ( int p = 1 ; p <= j; p++)
best = Math.min(
best, Math.max(dp[i - 1 ][p],
sum(arr, p, j - 1 )));
dp[i][j] = best;
}
}
// required
return dp[k][n];
}
// Driver code
public static void main(String args[])
{
int arr[] = { 10 , 20 , 60 , 50 , 30 , 40 };
// Calculate size of array.
int n = arr.length;
int k = 3 ;
System.out.println(findMax(arr, n, k));
}
} // This code is contributed by Sahil_Bansall |
# A DP based Python3 program for # painter's partition problem # function to calculate sum between # two indices in list def sum (arr, start, to):
total = 0
for i in range (start, to + 1 ):
total + = arr[i]
return total
# bottom up tabular dp def findMax(arr, n, k):
# initialize table
dp = [[ 0 for i in range (n + 1 )]
for j in range (k + 1 )]
# base cases
# k=1
for i in range ( 1 , n + 1 ):
dp[ 1 ][i] = sum (arr, 0 , i - 1 )
# n=1
for i in range ( 1 , k + 1 ):
dp[i][ 1 ] = arr[ 0 ]
# 2 to k partitions
for i in range ( 2 , k + 1 ): # 2 to n boards
for j in range ( 2 , n + 1 ):
# track minimum
best = 100000000
# i-1 th separator before position arr[p=1..j]
for p in range ( 1 , j + 1 ):
best = min (best, max (dp[i - 1 ][p],
sum (arr, p, j - 1 )))
dp[i][j] = best
# required
return dp[k][n]
# Driver Code arr = [ 10 , 20 , 60 , 50 , 30 , 40 ]
n = len (arr)
k = 3
print (findMax(arr, n, k))
# This code is contributed by ashutosh450 |
// A DP based C# program for // painter's partition problem using System;
class GFG {
// function to calculate sum between
// two indices in array
static int sum( int [] arr, int from , int to)
{
int total = 0;
for ( int i = from ; i <= to; i++)
total += arr[i];
return total;
}
// bottom up tabular dp
static int findMax( int [] arr, int n, int k)
{
// initialize table
int [, ] dp = new int [k + 1, n + 1];
// base cases
// k=1
for ( int i = 1; i <= n; i++)
dp[1, i] = sum(arr, 0, i - 1);
// n=1
for ( int i = 1; i <= k; i++)
dp[i, 1] = arr[0];
// 2 to k partitions
for ( int i = 2; i <= k; i++) { // 2 to n boards
for ( int j = 2; j <= n; j++) {
// track minimum
int best = int .MaxValue;
// i-1 th separator before position
// arr[p=1..j]
for ( int p = 1; p <= j; p++)
best = Math.Min(
best, Math.Max(dp[i - 1, p],
sum(arr, p, j - 1)));
dp[i, j] = best;
}
}
// required
return dp[k, n];
}
// Driver code
public static void Main()
{
int [] arr = { 10, 20, 60, 50, 30, 40 };
// Calculate size of array.
int n = arr.Length;
int k = 3;
Console.WriteLine(findMax(arr, n, k));
}
} // This code is contributed by vt_m |
<?php // A DP based PHP program for // painter's partition problem // function to calculate sum // between two indices in array function sum( $arr , $from , $to )
{ $total = 0;
for ( $i = $from ; $i <= $to ; $i ++)
$total += $arr [ $i ];
return $total ;
} // bottom up tabular dp function findMax( $arr , $n , $k )
{ // initialize table
$dp [ $k + 1][ $n + 1] = array ( 0 );
// base cases
// k=1
for ( $i = 1; $i <= $n ; $i ++)
$dp [1][ $i ] = sum( $arr , 0,
$i - 1);
// n=1
for ( $i = 1; $i <= $k ; $i ++)
$dp [ $i ][1] = $arr [0];
// 2 to k partitions
for ( $i = 2; $i <= $k ; $i ++)
{
// 2 to n boards
for ( $j = 2; $j <= $n ; $j ++)
{
// track minimum
$best = PHP_INT_MAX;
// i-1 th separator before
// position arr[p=1..j]
for ( $p = 1; $p <= $j ; $p ++)
$best = min( $best , max( $dp [ $i - 1][ $p ],
sum( $arr , $p , $j - 1)));
$dp [ $i ][ $j ] = $best ;
}
}
// required
return $dp [ $k ][ $n ];
} // Driver Code $arr = array (10, 20, 60,
50, 30, 40 );
$n = sizeof( $arr );
$k = 3;
echo findMax( $arr , $n , $k ) , "\n" ;
// This code is contributed by m_kit ?> |
<script> // A DP based Javascript program for
// painter's partition problem
// function to calculate sum between
// two indices in array
function sum(arr, from, to)
{
let total = 0;
for (let i = from; i <= to; i++)
total += arr[i];
return total;
}
// bottom up tabular dp
function findMax(arr, n, k)
{
// initialize table
let dp = new Array(k+1);
for (let i = 0; i < k + 1; i++)
{
dp[i] = new Array(n + 1);
}
// base cases
// k=1
for (let i = 1; i <= n; i++)
dp[1][i] = sum(arr, 0, i - 1);
// n=1
for (let i = 1; i <= k; i++)
dp[i][1] = arr[0];
// 2 to k partitions
for (let i = 2; i <= k; i++) { // 2 to n boards
for (let j = 2; j <= n; j++) {
// track minimum
let best = Number.MAX_VALUE;
// i-1 th separator before position arr[p=1..j]
for (let p = 1; p <= j; p++)
best = Math.min(best, Math.max(dp[i - 1][p],
sum(arr, p, j - 1)));
dp[i][j] = best;
}
}
// required
return dp[k][n];
}
// Driver code
let arr = [10, 20, 60, 50, 30, 40];
// Calculate size of array.
let n = arr.length;
let k = 3;
document.write(findMax(arr, n, k));
// This code is contributed by mukesh07.
</script> |
90
Time complexity: O(k∗N3)
Auxiliary Space: O(k*N)
Optimising Dynamic Programming Approach for Painter’s Problem using Precomputation
The time complexity of the above program is O(k∗N3). It can be easily brought down to O(k∗N2) by pre-computing the cumulative sums in an array, thus avoiding repeated calls to the sum function.
Below is the how we can achieve this optimisation:
int sum[n + 1] = { 0 };
// sum from 1 to i elements of arr for ( int i = 1; i <= n; i++)
sum[i] = sum[i - 1] + arr[i - 1];
for ( int i = 1; i <= n; i++)
dp[1][i] = sum[i];
// and using it to calculate the result as: best = min(best, max(dp[i - 1][p], sum[j] - sum[p])); |
int sum[] = new int [n + 1 ];
// sum from 1 to i elements of arr for ( int i = 1 ; i <= n; i++)
sum[i] = sum[i - 1 ] + arr[i - 1 ];
for ( int i = 1 ; i <= n; i++)
dp[ 1 ][i] = sum[i];
// and using it to calculate the result as: best = Math.min(best, Math.max(dp[i - 1 ][p], sum[j] - sum[p]));
// This code is contributed by divyesh072019. |
sum = [ 0 ] * (n + 1 )
# sum from 1 to i elements of arr for i in range ( 1 , n + 1 ):
sum [i] = sum [i - 1 ] + arr[i - 1 ]
for i in range ( 1 , n + 1 ):
dp[ 1 ][i] = sum [i]
# and using it to calculate the result as: best = min (best, max (dp[i - 1 ][p], sum [j] - sum [p]))
# This code is contributed by kraanzu. |
int [] sum = new int [n + 1];
// sum from 1 to i elements of arr for ( int i = 1; i <= n; i++)
sum[i] = sum[i - 1] + arr[i - 1];
for ( int i = 1; i <= n; i++)
dp[1, i] = sum[i];
// and using it to calculate the result as: best = Math.Min(best, Math.Max(dp[i - 1][p], sum[j] - sum[p]));
// This code is contributed by divyeshrabadiya07. |
<script> let sum = new Array(n+1);
// sum from 1 to i elements of arr for (let i = 1; i <= n; i++)
sum[i] = sum[i-1] + arr[i-1];
for (let i = 1; i <= n; i++)
dp[1][i] = sum[i];
// and using it to calculate the result as: best = Math.min(best, Math.max(dp[i-1][p], sum[j] - sum[p])); // This code is contributed by Saurabh Jaiswal. </script> |
Note: Though here we consider dividing A into k or fewer partitions, we can observe that the optimal case always occurs when we divide A into exactly k partitions.
So we can use:
for ( int i = k - 1; i <= n; i++)
best = min(best, max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
|
for ( int i = k - 1 ; i <= n; i++)
best = Math.min(best, Math.max(partition(arr, i, k - 1 ),
sum(arr, i, n - 1 )));
// This code is contributed by pratham76. |
for i range (k - 1 , n + 1 ):
best = min (best, max (partition(arr, i, k - 1 ), sum (arr, i, n - 1 )))
# This code is contributed by Aman Kumar. |
for ( int i = k - 1; i <= n; i++)
best = Math.Min(best, Math.Max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
// This code is contributed by rutvik_56 |
for ( var i = k - 1; i <= n; i++)
best = Math.min(best, Math.max(partition(arr, i, k - 1),
sum(arr, i, n - 1)));
// This code is contributed by Ankita saini |
Exercise:
Can you come up with a solution to this Painter’s Problem using Binary Search?