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Minimum sum of absolute difference of pairs of two arrays
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Minimum sum of product of two arrays

Last Updated : 14 Jul, 2023
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Find the minimum sum of Products of two arrays of the same size, given that k modifications are allowed on the first array. In each modification, one array element of the first array can either be increased or decreased by 2.
Examples: 

Input : a[] = {1, 2, -3}         b[]  = {-2, 3, -5}            k = 5 Output : -31 Explanation: Here n = 3 and k = 5.  So, we modified a[2], which is -3 and  increased it by 10 (as 5 modifications  are allowed). Final sum will be : (1 * -2) + (2 * 3) + (7 * -5)    -2    +    6    -    35              -31 (which is the minimum sum of the array  with given conditions)  Input : a[] = {2, 3, 4, 5, 4}         b[] = {3, 4, 2, 3, 2}         k = 3 Output : 25 Explanation:  Here, total numbers are 5 and total  modifications allowed are 3. So, modify  a[1], which is 3 and decreased it by 6  (as 3 modifications are allowed). Final sum will be : (2 * 3) + (-3 * 4) + (4 * 2) + (5 * 3) + (4 * 2)    6    –    12    +    8    +    15   +    8                         25 (which is the minimum sum of the array with  given conditions) 

Since we need to minimize the product sum, we find the maximum product and reduce it. By taking some examples, we observe that making 2*k changes to only one element is enough to get the minimum sum. We will further see why this works but first, let us try to understand the intuition behind doing an increase or decrease of 2*k on any element.

If you want to make the sum of all the products as minimum as possible then thinking greedily we will try to minimize the product at every step possible.

a[] = {1, 2, -3}

b[] = {-2, 3, -5}

At index = 0, the original product is (1*-2) = -2 If we want to decrease it further we would try to increase the value of a[0] in order to increase the -ve magnitude

At index = 1, the original product is (2*3) = 6 here there is only one way to decrease the product which is by decreasing a[1] in order to bring the product to -ve or lesser +ve magnitude.

At index = 2, the original product is (-3*-5) = 15, to decrease the product we need to increase a[2] to make the product -ve

Based on the needs we either increase or decrease an element by 2

Why are we applying 2*k operations on a single element only?

The question might have come to your mind why are we applying 2*k operations (either reducing or increasing) on a single element only, why not apply +2 on some ith index and -4 on some jth index and then -2 on some kth index to find out the minimum product sum. Wouldn’t there be a possibility that applying operations on different elements fetch us the optimal answer?

Let us try to understand the same with an example

a[] = {-4, -3, 2, 8, 9}

b[] = {7, -6, 4, 2, -3}

K = 3

Now if I apply 2*k operations on my 0th index of a then a[0] = a[0] – 2*k = -10 so the product = -10*7 = -70

Had it been applied in a different manner such as -2 on the 0th index, +2 on the 1th index, and -2 on the 3th index then array a would be a[] ={-6, -1, 2, 6, 9} and the products at respective indices would be -42, 6, and 12 so our overall reduction = -24 which is less than the case when 2*k operations are being applied on a single element.

Just think in the way that if applying an operation on any element decreases your product then applying the rest of the operation on the same element would further decrease your product and eventually your sum and that’s the most optimal way.

I would suggest you write down a few test cases of your own and try applying operations in different ways.

Based on this observation, we consider every element as the element on which we apply all k operations and keep track of the element that reduces the result to a minimum.  

C++




// CPP program to find minimum sum of product of two arrays
// with k operations allowed on first array.
#include <bits/stdc++.h>
using namespace std;
 
// Function to find the minimum product
int minproduct(int a[], int b[], int n, int k)
{
    int diff = 0, res = 0;
    int temp;
    for (int i = 0; i < n; i++) {
 
        // Find product of current elements and update
        // result.
        int pro = a[i] * b[i];
        res = res + pro;
 
        // If both product and b[i] are negative, we must
        // increase value of a[i] to minimize result.
        if (pro < 0 && b[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
 
        // If both product and a[i] are negative, we must
        // decrease value of a[i] to minimize result.
        else if (pro < 0 && a[i] < 0)
            temp = (a[i] - 2 * k) * b[i];
 
        // Similar to above two cases for positive product.
        else if (pro > 0 && a[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
        else if (pro > 0 && a[i] > 0)
            temp = (a[i] - 2 * k) * b[i];
 
        // Check if current difference becomes higher than
        // the maximum difference so far.
        int d = abs(pro - temp);
        if (d > diff)
            diff = d;
    }
 
    return res - diff;
}
 
// Driver function
int main()
{
    int a[] = { 2, 3, 4, 5, 4 };
    int b[] = { 3, 4, 2, 3, 2 };
    int n = 5, k = 3;
    cout << minproduct(a, b, n, k) << endl;
    return 0;
}
 
// This code is contributed by Sania Kumari Gupta
 
 

C




// C program to find minimum sum of product
// of two arrays with k operations allowed on
// first array.
#include <stdio.h>
#include<stdlib.h>
 
// Function to find the minimum product
int minproduct(int a[], int b[], int n, int k)
{
    int diff = 0, res = 0;
    int temp;
    for (int i = 0; i < n; i++) {
        // Find product of current elements and update
        // result.
        int pro = a[i] * b[i];
        res = res + pro;
 
        // If both product and b[i] are negative, we must
        // increase value of a[i] to minimize result.
        if (pro < 0 && b[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
 
        // If both product and a[i] are negative, we must
        // decrease value of a[i] to minimize result.
        else if (pro < 0 && a[i] < 0)
            temp = (a[i] - 2 * k) * b[i];
 
        // Similar to above two cases for positive product.
        else if (pro > 0 && a[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
        else if (pro > 0 && a[i] > 0)
            temp = (a[i] - 2 * k) * b[i];
 
        // Check if current difference becomes higher than
        // the maximum difference so far.
        int d = abs(pro - temp);
        if (d > diff)
            diff = d;
    }
 
    return res - diff;
}
 
// Driver function
int main()
{
    int a[] = { 2, 3, 4, 5, 4 };
    int b[] = { 3, 4, 2, 3, 2 };
    int n = 5, k = 3;
    printf("%d ",minproduct(a, b, n, k));
    return 0;
}
 
// This code is contributed by Sania Kumari Gupta
 
 

Java




// Java program to find minimum sum of product of two arrays
// with k operations allowed on first array.
import java.math.*;
 
class GFG {
 
    // Function to find the minimum product
    static int minproduct(int a[], int b[], int n, int k)
    {
        int diff = 0, res = 0;
        int temp = 0;
        for (int i = 0; i < n; i++) {
 
            // Find product of current elements and update
            // result.
            int pro = a[i] * b[i];
            res = res + pro;
 
            // If both product and b[i] are negative, we
            // must increase value of a[i] to minimize
            // result.
            if (pro < 0 && b[i] < 0)
                temp = (a[i] + 2 * k) * b[i];
 
            // If both product and a[i] are negative, we
            // must decrease value of a[i] to minimize
            // result.
            else if (pro < 0 && a[i] < 0)
                temp = (a[i] - 2 * k) * b[i];
 
            // Similar to above two cases for positive
            // product.
            else if (pro > 0 && a[i] < 0)
                temp = (a[i] + 2 * k) * b[i];
            else if (pro > 0 && a[i] > 0)
                temp = (a[i] - 2 * k) * b[i];
 
            // Check if current difference becomes higher
            // than the maximum difference so far.
            int d = Math.abs(pro - temp);
            if (d > diff)
                diff = d;
        }
 
        return res - diff;
    }
 
    // Driver function
    public static void main(String[] args)
    {
        int a[] = { 2, 3, 4, 5, 4 };
        int b[] = { 3, 4, 2, 3, 2 };
        int n = 5, k = 3;
        System.out.println(minproduct(a, b, n, k));
    }
}
 
// This code is contributed by Sania Kumari Gupta
 
 

Python3




# Python program to find
# minimum sum of product
# of two arrays with k
# operations allowed on
# first array.
 
# Function to find the minimum product
def minproduct(a,b,n,k):
 
    diff = 0
    res = 0
    for i in range(n):
 
        # Find product of current
        # elements and update result.
        pro = a[i] * b[i]
        res = res + pro
 
        # If both product and
        # b[i] are negative,
        # we must increase value
        # of a[i] to minimize result.
        if (pro < 0 and b[i] < 0):
            temp = (a[i] + 2 * k) * b[i]
 
        # If both product and
        # a[i] are negative,
        # we must decrease value
        # of a[i] to minimize result.
        elif (pro < 0 and a[i] < 0):
            temp = (a[i] - 2 * k) * b[i]
 
        # Similar to above two cases
        # for positive product.
        elif (pro > 0 and a[i] < 0):
            temp = (a[i] + 2 * k) * b[i]
        elif (pro > 0 and a[i] > 0):
            temp = (a[i] - 2 * k) * b[i]
 
        # Check if current difference
        # becomes higher
        # than the maximum difference so far.
        d = abs(pro - temp)
 
        if (d > diff):
            diff = d      
    return res - diff
 
# Driver function
a = [ 2, 3, 4, 5, 4 ]
b = [ 3, 4, 2, 3, 2 ]
n = 5
k = 3
 
print(minproduct(a, b, n, k))
 
# This code is contributed
# by Azkia Anam.
 
 

C#




// C# program to find minimum sum
// of product of two arrays with k
// operations allowed on first array.
using System;
 
class GFG {
 
    // Function to find the minimum product
    static int minproduct(int []a, int []b,
                                int n, int k)
    {
        int diff = 0, res = 0;
        int temp = 0;
        for (int i = 0; i < n; i++)
        {
     
            // Find product of current elements
            // and update result.
            int pro = a[i] * b[i];
            res = res + pro;
     
            // If both product and b[i] are
            // negative, we must increase value
            // of a[i] to minimize result.
            if (pro < 0 && b[i] < 0)
                temp = (a[i] + 2 * k) * b[i];
     
            // If both product and a[i] are
            // negative, we must decrease value
            // of a[i] to minimize result.
            else if (pro < 0 && a[i] < 0)
                temp = (a[i] - 2 * k) * b[i];
     
            // Similar to above two cases
            // for positive product.
            else if (pro > 0 && a[i] < 0)
                temp = (a[i] + 2 * k) * b[i];
            else if (pro > 0 && a[i] > 0)
                temp = (a[i] - 2 * k) * b[i];
     
            // Check if current difference
            // becomes higher than the maximum
            // difference so far.
            int d = Math.Abs(pro - temp);
            if (d > diff)
                diff = d;
        }
     
        return res - diff;
    }
     
    // Driver function
    public static void Main()
    {
        int []a = { 2, 3, 4, 5, 4 };
        int []b = { 3, 4, 2, 3, 2 };
        int n = 5, k = 3;
         
        Console.WriteLine(minproduct(a, b, n, k));
    }
}
 
// This code is contributed by vt_m.
 
 

Javascript




<script>
// Javascript program to find minimum sum
// of product of two arrays with k
// operations allowed on first array.
 
// Function to find the minimum product
function minproduct(a, b, n, k)
{
    let diff = 0, res = 0;
    let temp = 0;
    for (let i = 0; i < n; i++)
    {
  
        // Find product of current elements
        // and update result.
        let pro = a[i] * b[i];
        res = res + pro;
  
        // If both product and b[i] are
        // negative, we must increase value
        // of a[i] to minimize result.
        if (pro < 0 && b[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
  
        // If both product and a[i] are
        // negative, we must decrease value
        // of a[i] to minimize result.
        else if (pro < 0 && a[i] < 0)
            temp = (a[i] - 2 * k) * b[i];
  
        // Similar to above two cases
        // for positive product.
        else if (pro > 0 && a[i] < 0)
            temp = (a[i] + 2 * k) * b[i];
        else if (pro > 0 && a[i] > 0)
            temp = (a[i] - 2 * k) * b[i];
  
        // Check if current difference
        // becomes higher than the maximum
        // difference so far.
        let d = Math.abs(pro - temp);
        if (d > diff)
            diff = d;   
    }
  
    return res - diff;
}
     
// Driver code
        let a = [ 2, 3, 4, 5, 4 ];
    let b = [ 3, 4, 2, 3, 2 ];
    let n = 5, k = 3;
    document.write(minproduct(a, b, n, k));
    
   // This code is contributed by sanjoy_62.
</script>
 
 

PHP




<?php
// PHP program to find minimum sum of product
// of two arrays with k operations allowed on
// first array.
 
// Function to find the minimum product
function minproduct( $a, $b, $n, $k)
{
    $diff = 0; $res = 0;
    $temp;
    for ( $i = 0; $i < $n; $i++) {
 
        // Find product of current
        // elements and update
        // result.
        $pro = $a[$i] * $b[$i];
        $res = $res + $pro;
 
        // If both product and b[i]
        // are negative, we must
        // increase value of a[i]
        // to minimize result.
        if ($pro < 0 and $b[$i] < 0)
            $temp = ($a[$i] + 2 * $k) *
                                 $b[$i];
 
        // If both product and
        // a[i] are negative,
        // we must decrease value
        // of a[i] to minimize
        // result.
        else if ($pro < 0 and $a[$i] < 0)
            $temp = ($a[$i] - 2 * $k) * $b[$i];
 
        // Similar to above two
        // cases for positive
        // product.
        else if ($pro > 0 and $a[$i] < 0)
            $temp = ($a[$i] + 2 * $k) * $b[$i];
        else if ($pro > 0 and $a[$i] > 0)
            $temp = ($a[$i] - 2 * $k) * $b[$i];
 
        // Check if current difference becomes higher
        // than the maximum difference so far.
        $d = abs($pro - $temp);
        if ($d > $diff)
            $diff = $d;
    }
 
    return $res - $diff;
}
 
    // Driver Code
    $a = array(2, 3, 4, 5, 4 ,0);
    $b =array(3, 4, 2, 3, 2);
    $n = 5;
    $k = 3;
    echo minproduct($a, $b, $n, $k);
     
// This code is contributed by anuj_67.
?>
 
 

Output :

25 

Time Complexity: O(n)
Auxiliary Space: O(1)


 



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    • Partition into two subsets of lengths K and (N - k) such that the difference of sums is maximum
      Given an array of non-negative integers of length N and an integer K. Partition the given array into two subsets of length K and N - K so that the difference between the sum of both subsets is maximum. Examples : Input : arr[] = {8, 4, 5, 2, 10} k = 2 Output : 17 Explanation : Here, we can make firs
      7 min read

    Greedy algorithm on Operating System

    • Program for First Fit algorithm in Memory Management
      Prerequisite : Partition Allocation MethodsIn the first fit, the partition is allocated which is first sufficient from the top of Main Memory.Example : Input : blockSize[] = {100, 500, 200, 300, 600}; processSize[] = {212, 417, 112, 426};Output:Process No. Process Size Block no. 1 212 2 2 417 5 3 11
      8 min read

    • Program for Best Fit algorithm in Memory Management
      Prerequisite : Partition allocation methodsBest fit allocates the process to a partition which is the smallest sufficient partition among the free available partitions. Example: Input : blockSize[] = {100, 500, 200, 300, 600}; processSize[] = {212, 417, 112, 426}; Output: Process No. Process Size Bl
      8 min read

    • Program for Worst Fit algorithm in Memory Management
      Prerequisite : Partition allocation methodsWorst Fit allocates a process to the partition which is largest sufficient among the freely available partitions available in the main memory. If a large process comes at a later stage, then memory will not have space to accommodate it. Example: Input : blo
      8 min read

    • Program for Shortest Job First (or SJF) CPU Scheduling | Set 1 (Non- preemptive)
      The shortest job first (SJF) or shortest job next, is a scheduling policy that selects the waiting process with the smallest execution time to execute next. SJN, also known as Shortest Job Next (SJN), can be preemptive or non-preemptive. Characteristics of SJF Scheduling: Shortest Job first has the
      13 min read

    • Job Scheduling with two jobs allowed at a time
      Given a 2d array jobs[][] of order n * 2, where each element jobs[i], contains two integers, representing the start and end time of the job. Your task is to check if it is possible to complete all the jobs, provided that two jobs can be done simultaneously at a particular moment. Note: If a job star
      6 min read

    • Optimal Page Replacement Algorithm
      In operating systems, whenever a new page is referred and not present in memory, page fault occurs, and Operating System replaces one of the existing pages with newly needed page. Different page replacement algorithms suggest different ways to decide which page to replace. The target for all algorit
      3 min read

    Greedy algorithm on Graph

    • Prim’s Algorithm for Minimum Spanning Tree (MST)
      Prim’s algorithm is a Greedy algorithm like Kruskal's algorithm. This algorithm always starts with a single node and moves through several adjacent nodes, in order to explore all of the connected edges along the way. The algorithm starts with an empty spanning tree. The idea is to maintain two sets
      15+ min read

    • Boruvka's algorithm | Greedy Algo-9
      We have discussed the following topics on Minimum Spanning Tree.Applications of Minimum Spanning Tree Problem Kruskal’s Minimum Spanning Tree Algorithm Prim’s Minimum Spanning Tree AlgorithmIn this post, Boruvka's algorithm is discussed. Like Prim's and Kruskal's, Boruvka’s algorithm is also a Greed
      15+ min read

    • Dial's Algorithm (Optimized Dijkstra for small range weights)
      Dijkstra’s shortest path algorithm runs in O(Elog V) time when implemented with adjacency list representation (See C implementation and STL based C++ implementations for details). Input : Source = 0, Maximum Weight W = 14Output : Vertex Distance from Source 0 0 1 4 2 12 3 19 4 21 5 11 6 9 7 8 8 14 C
      15+ min read

    • Minimum cost to connect all cities
      There are n cities and there are roads in between some of the cities. Somehow all the roads are damaged simultaneously. We have to repair the roads to connect the cities again. There is a fixed cost to repair a particular road. Input is in the form of edges {u, v, w} where, u and v are city indices.
      7 min read

    • Number of single cycle components in an undirected graph
      Given a set of 'n' vertices and 'm' edges of an undirected simple graph (no parallel edges and no self-loop), find the number of single-cycle components present in the graph. A single-cyclic component is a graph of n nodes containing a single cycle through all nodes of the component. Example: Let us
      9 min read

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