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Find the maximum cost of an array of pairs choosing at most K pairs

Given an array of pairs arr[], the task is to find the maximum cost choosing at most K pairs. The cost of an array of pairs is defined as product of the sum of first elements of the selected pair and the minimum among the second elements of the selected pairs. For example, if the following pairs are selected (3, 7), (9, 2) and (2, 5), then the cost will be (3+9+2)*(2) = 28.
Examples: 

Input: arr[] = { {4, 7}, {15, 1}, {3, 6}, {6, 8} }, K = 3 
Output: 78 
The pairs 1, 3 and 4 are selected, therefore the cost = (4 + 3 + 6) * 6 = 78. 

Input: arr[] = { {62, 21}, {31, 16}, {19, 2}, {32, 19}, {12, 17} }, K = 4 
Output: 2192 

Approach: If the second element of a pair is fixed in the answer, then K-1(or less) other pairs are to be selected from those pairs whose second element is greater or equal to the fixed second element and the answer will be maximum if those are chosen such that the sum of first elements is maximum. So, sort the array according to second element and then iterate in descending order taking maximum sum of the first element of K pairs(or less). The maximum sum of first element K pairs can be taken with the help of Set data structure. 
Below is the implementation of the above approach:

CPP




// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
 
// Driver function to sort the array elements
// by second element of pairs
bool sortbysec(const pair<int, int>& a,
               const pair<int, int>& b)
{
    return (a.second < b.second);
}
 
// Function that returns the maximum cost of
// an array of pairs choosing at most K pairs.
int maxCost(pair<int, int> a[], int N, int K)
{
    // Initialize result and temporary sum variables
    int res = 0, sum = 0;
 
    // Initialize Set to store K greatest
    // element for maximum sum
    set<pair<int, int> > s;
 
    // Sort array by second element
    sort(a, a + N, sortbysec);
 
    // Iterate in descending order
    for (int i = N - 1; i >= 0; --i) {
        s.insert(make_pair(a[i].first, i));
        sum += a[i].first;
        while (s.size() > K) {
            auto it = s.begin();
            sum -= it->first;
            s.erase(it);
        }
 
        res = max(res, sum * a[i].second);
    }
 
    return res;
}
 
// Driver Code
int main()
{
    pair<int, int> arr[] = { { 12, 3 }, { 62, 21 }, { 31, 16 },
                             { 19, 2 }, { 32, 19 }, { 12, 17 },
                             { 1, 7 } };
 
    int N = sizeof(arr) / sizeof(arr[0]);
 
    int K = 3;
 
    cout << maxCost(arr, N, K);
 
    return 0;
}


Java




// Function that returns the maximum cost of an array of pairs choosing at most K pairs.
public static int maxCost(final Pair<Integer, Integer>[] a, final int N, final int K) {
    // Initialize result and temporary sum variables
    int res = 0, sum = 0;
 
    // Initialize Set to store K greatest element for maximum sum
    final Set<Pair<Integer, Integer>> s = new TreeSet<Pair<Integer, Integer>>(
            (x, y) -> Integer.compare(x.getKey(), y.getKey()));
 
    // Sort array by second element
    Arrays.sort(a, 0, N, Main::sortbysec);
 
    // Iterate in descending order
    for (int i = N - 1; i >= 0; --i) {
        s.add(new Pair<>(a[i].getKey(), i));
        sum += a[i].getKey();
        while (s.size() > K) {
            final Iterator<Pair<Integer, Integer>> it = s.iterator();
            final Pair<Integer, Integer> p = it.next();
            sum -= p.getKey();
            it.remove();
        }
 
        res = Math.max(res, sum * a[i].getValue());
    }
 
    return res;
}
 
// Driver Code
public static void main(final String[] args) {
    final Pair<Integer, Integer>[] arr = new Pair[] { new Pair<>(12, 3), new Pair<>(62, 21), new Pair<>(31, 16),
            new Pair<>(19, 2), new Pair<>(32, 19), new Pair<>(12, 17), new Pair<>(1, 7) };
    final int N = arr.length;
    final int K = 3;
 
    System.out.println(maxCost(arr, N, K));
}


Python3




import heapq
 
# Function that returns the maximum cost of an array of pairs choosing at most K pairs.
def maxCost(a, N, K):
    # Initialize result and temporary sum variables
    res = 0
    sum = 0
 
    # Initialize heap to store K greatest element for maximum sum
    heap = []
 
    # Sort array by second element
    a = sorted(a, key=lambda x: x[1])
 
    # Iterate in descending order
    for i in range(N-1, -1, -1):
        heapq.heappush(heap, a[i][0])
        sum += a[i][0]
 
        while len(heap) > K:
            sum -= heapq.heappop(heap)
 
        res = max(res, sum * a[i][1])
 
    return res
 
# Driver Code
if __name__ == "__main__":
    arr = [(12, 3), (62, 21), (31, 16), (19, 2), (32, 19), (12, 17), (1, 7)]
    N = len(arr)
    K = 3
    print(maxCost(arr, N, K))
# This code is contributed by Prince Kumar


C#




// C# porgrm for the above approach
 
using System;
using System.Collections.Generic;
 
public class Pair<T1, T2> {
    public T1 Key;
    public T2 Value;
    public Pair(T1 key, T2 value) {
        Key = key;
        Value = value;
    }
}
 
public class Program {
    // Custom comparator to sort pairs by first element in descending order
    public static int SortByFirstDesc(Pair<int, int> a, Pair<int, int> b) {
        return b.Key.CompareTo(a.Key);
    }
 
    // Function that returns the maximum cost of an array of pairs choosing at most K pairs.
    public static int MaxCost(Pair<int, int>[] a, int N, int K) {
        // Initialize result and temporary sum variables
        int res = 0, sum = 0;
 
        // Initialize Set to store K greatest element for maximum sum
        SortedSet<Pair<int, int>> s = new SortedSet<Pair<int, int>>(
            Comparer<Pair<int, int>>.Create(SortByFirstDesc));
 
        // Sort array by first element in descending order
        Array.Sort(a, 0, N, Comparer<Pair<int, int>>.Create(SortByFirstDesc));
 
        // Iterate in descending order
        for (int i = 0; i < N; ++i) {
            s.Add(new Pair<int, int>(a[i].Key, i));
            sum += a[i].Key;
            while (s.Count > K) {
                Pair<int, int> p = s.Min;
                sum -= p.Key;
                s.Remove(p);
            }
 
            res = Math.Max(res, sum * a[i].Value);
        }
 
        return res;
    }
 
    // Driver Code
    public static void Main() {
        Pair<int, int>[] arr = new Pair<int, int>[] {
            new Pair<int, int>(12, 3),
            new Pair<int, int>(62, 21),
            new Pair<int, int>(31, 16),
            new Pair<int, int>(19, 2),
            new Pair<int, int>(32, 19),
            new Pair<int, int>(12, 17),
            new Pair<int, int>(1, 7)
        };
        int N = arr.Length;
        int K = 3;
 
        Console.WriteLine(MaxCost(arr, N, K));
    }
}
 
// This code is contributed by adityasharmadev01


Javascript




// Javascript program for the above approach
 
// Function to sort the array elements by second element of pairs
function sortbysec(a, b) {
  return a[1] - b[1];
}
 
// Function that returns the maximum cost of
// an array of pairs choosing at most K pairs.
function maxCost(a, N, K) {
  // Initialize result and temporary sum variables
  let res = 0;
  let sum = 0;
 
  // Initialize array to store K greatest element for maximum sum
  let arr = [];
 
  // Sort array by second element
  a.sort(sortbysec);
 
  // Iterate in descending order
  for (let i = N - 1; i >= 0; --i) {
    arr.push([a[i][0], i]);
    sum += a[i][0];
    while (arr.length > K) {
      let min = Infinity;
      let idx = -1;
      for (let j = 0; j < arr.length; j++) {
        if (arr[j][0] < min) {
          min = arr[j][0];
          idx = j;
        }
      }
      sum -= arr[idx][0];
      arr.splice(idx, 1);
    }
 
    res = Math.max(res, sum * a[i][1]);
  }
 
  return res;
}
 
// Driver Code
const arr = [
  [12, 3],
  [62, 21],
  [31, 16],
  [19, 2],
  [32, 19],
  [12, 17],
  [1, 7],
];
 
const N = arr.length;
const K = 3;
 
console.log(maxCost(arr, N, K));
 
// This code is contributed by princekumaras


Output: 

2000

 

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

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Ted Musemwa
As a software developer I’m interested in the intersection of computational thinking and design thinking when solving human problems. As a professional I am guided by the principles of experiential learning; experience, reflect, conceptualise and experiment.
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