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Maximize product of min value of subarray and sum of subarray over all subarrays of length K

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  • Difficulty Level : Medium
  • Last Updated : 23 Nov, 2021

Given an array arr[] of N integers, the task is to find the maximum possible value of (min * sum) among all possible subarrays having K elements, where min denotes the smallest integer of the subarray and sum denotes the sum of all elements of the subarray.

Example

Input: arr[] = {1, 2, 3, 2}, K = 3
Output: 14
Explanation: For the subarray {2, 3, 2}, the score is given as min(2, 3, 2) * sum(2, 3, 2) = 2 * 7 = 14, which is the maximum possible.

Input: arr[] = {3, 1, 5, 6, 4, 2}, K = 2
Output: 55

 

Approach: The above problem can be solved with the help of the sliding window technique by maintaining a window of K elements during the traversal of the array and keeping track of the minimum element and the sum of all elements in the current window in variables minimum and sum respectively. The minimum of all the K-sized subarrays can be calculated using a multiset data structure similar to the algorithm discussed here and the sum can be calculated using the algorithm discussed here. The maximum value of minimum * sum over all K-sized windows is the required answer.

Below is the implementation of the above approach:

C++




// C++ implementation for the above approach
#include <bits/stdc++.h>
using namespace std;
 
// Function to the maximum value of min * sum
// over all possible subarrays of K elements
int maxMinSum(vector<int> arr, int K)
{
    // Store the array size
    int N = arr.size();
 
    // Multiset data structure to calculate the
    // minimum over all K sized subarrays
    multiset<int> s;
 
    // Stores the sum of the surrent window
    int sum = 0;
 
    // Loop to calculate the sum and min of the
    // 1st window of size K
    for (int i = 0; i < K; i++) {
        s.insert(arr[i]);
        sum += arr[i];
    }
 
    // Stores the required answer
    int ans = sum * (*s.begin());
 
    // Loop to iterate over the remaining windows
    for (int i = K; i < N; i++) {
 
        // Add the current value and remove the
        // (i-K)th value from the sum
        sum += (arr[i] - arr[i - K]);
 
        // Update the set
        s.erase(s.find(arr[i - K]));
        s.insert(arr[i]);
 
        // Update answer
        ans = max(ans, sum * (*s.begin()));
    }
 
    // Return Answer
    return ans;
}
 
// Driver Code
int main()
{
    vector<int> arr = { 3, 1, 5, 6, 4, 2 };
    int K = 2;
 
    cout << maxMinSum(arr, K);
 
    return 0;
}

Java




// Java implementation for the above approach
import java.util.HashSet;
 
class GFG {
 
    // Function to the maximum value of min * sum
    // over all possible subarrays of K elements
    public static int maxMinSum(int[] arr, int K)
    {
       
        // Store the array size
        int N = arr.length;
 
        // Multiset data structure to calculate the
        // minimum over all K sized subarrays
        HashSet<Integer> s = new HashSet<Integer>();
 
        // Stores the sum of the surrent window
        int sum = 0;
 
        // Loop to calculate the sum and min of the
        // 1st window of size K
        for (int i = 0; i < K; i++) {
            s.add(arr[i]);
            sum += arr[i];
        }
 
        // Stores the required answer
        int ans = sum * (s.iterator().next());
 
        // Loop to iterate over the remaining windows
        for (int i = K; i < N; i++) {
 
            // Add the current value and remove the
            // (i-K)th value from the sum
            sum += (arr[i] - arr[i - K]);
 
            // Update the set
            if (s.contains(arr[i - K]))
                s.remove(arr[i - K]);
            s.add(arr[i]);
 
            // Update answer
            ans = Math.max(ans, sum * (s.iterator().next()));
        }
 
        // Return Answer
        return ans;
    }
 
    // Driver Code
    public static void main(String args[]) {
        int[] arr = { 3, 1, 5, 6, 4, 2 };
        int K = 2;
 
        System.out.println(maxMinSum(arr, K));
    }
}
 
// This code is contributed by saurabh_jaiswal.

Python3




# python implementation for the above approach
 
# Function to the maximum value of min * sum
# over all possible subarrays of K elements
def maxMinSum(arr, K):
 
    # Store the array size
    N = len(arr)
 
    # Multiset data structure to calculate the
    # minimum over all K sized subarrays
    s = set()
 
    # Stores the sum of the surrent window
    sum = 0
 
    # Loop to calculate the sum and min of the
    # 1st window of size K
    for i in range(0, K):
        s.add(arr[i])
        sum += arr[i]
 
    # Stores the required answer
    ans = sum * (list(s)[0])
 
    # Loop to iterate over the remaining windows
    for i in range(K, N):
 
       # Add the current value and remove the
       # (i-K)th value from the sum
        sum += (arr[i] - arr[i - K])
 
        # Update the set
        if arr[i-K] in s:
            s.remove(arr[i-K])
 
        s.add(arr[i])
 
        # Update answer
        ans = max(ans, sum * (list(s)[0]))
 
        # Return Answer
    return ans
 
# Driver Code
if __name__ == "__main__":
 
    arr = [3, 1, 5, 6, 4, 2]
    K = 2
 
    print(maxMinSum(arr, K))
 
    # This code is contributed by rakeshsahni

C#




// C# implementation for the above approach
using System;
using System.Collections.Generic;
using System.Linq;
 
class GFG {
 
    // Function to the maximum value of min * sum
    // over all possible subarrays of K elements
    public static int maxMinSum(int[] arr, int K)
    {
       
        // Store the array size
        int N = arr.Length;
 
        // Multiset data structure to calculate the
        // minimum over all K sized subarrays
        HashSet<int> s = new HashSet<int>();
 
        // Stores the sum of the surrent window
        int sum = 0;
 
        // Loop to calculate the sum and min of the
        // 1st window of size K
        for (int i = 0; i < K; i++) {
            s.Add(arr[i]);
            sum += arr[i];
        }
 
        // Stores the required answer
        int ans = sum * (s.ToList<int>()[0]);
 
 
        // Loop to iterate over the remaining windows
        for (int i = K; i < N; i++) {
 
            // Add the current value and remove the
            // (i-K)th value from the sum
            sum += (arr[i] - arr[i - K]);
 
            // Update the set
            if (s.Contains(arr[i - K]))
                s.Remove(arr[i - K]);
            s.Add(arr[i]);
 
            // Update answer
            ans = Math.Max(ans, sum * (s.ToList<int>()[0]));
        }
 
        // Return Answer
        return ans;
    }
 
    // Driver Code
    public static void Main() {
        int[] arr = { 3, 1, 5, 6, 4, 2 };
        int K = 2;
 
        Console.Write(maxMinSum(arr, K));
    }
}
 
// This code is contributed by saurabh_jaiswal.

Javascript




<script>
 
       // JavaScript Program to implement
       // the above approach
       function MultiSet() {
           let tm = {}; // treemap: works for key >= 0
           return { add, erase, first }
           function add(x) {
               tm[x] ? tm[x]++ : tm[x] = 1;
           }
 
           function erase(x) {
               delete tm[x];
           }
 
           function first() {
               let a = Object.keys(tm);
               return a[0] - '0';
           }
 
       }
 
 
       // Function to the maximum value of min * sum
       // over all possible subarrays of K elements
       function maxMinSum(arr, K) {
           // Store the array size
           let N = arr.length;
 
           // Multiset data structure to calculate the
           // minimum over all K sized subarrays
           let s = new MultiSet();
 
           // Stores the sum of the surrent window
           let sum = 0;
 
           // Loop to calculate the sum and min of the
           // 1st window of size K
           for (let i = 0; i < K; i++) {
               s.add(arr[i]);
               sum += arr[i];
           }
 
           // Stores the required answer
           let ans = sum * (s.first());
 
           // Loop to iterate over the remaining windows
           for (let i = K; i < N; i++) {
 
               // Add the current value and remove the
               // (i-K)th value from the sum
               sum += (arr[i] - arr[i - K]);
 
               // Update the set
               s.erase(arr[i - K]);
               s.add(arr[i]);
 
               // Update answer
               ans = Math.max(ans, sum * (s.first()));
           }
 
           // Return Answer
           return ans;
       }
 
       // Driver Code
 
       let arr = [3, 1, 5, 6, 4, 2];
       let K = 2;
 
       document.write(maxMinSum(arr, K));
 
 
   // This code is contributed by Potta Lokesh
   </script>

 
 

Output: 
55

 

 

Time Complexity: O(N*log N)
Auxiliary Space: O(N)

 


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