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📜  最小化两个数组之间的交换,使得第一个数组的总和超过第二个数组的总和

📅  最后修改于: 2021-09-06 06:36:50             🧑  作者: Mango

给定两个大小分别为NM 的数组arr1[]arr2[] ,任务是计算两个数组之间所需的最小交换次数,以使数组arr1 [] 的总和大于arr2 [] .

例子:

方法:给定的问题可以通过对两个数组进行排序并执行交换以最大化arr1[]的总和来解决。请按照以下步骤解决问题:

  • 对两个数组进行排序并分别计算数组的总和为sum1sum2
  • 将变量count初始化为0以存储所需的交换次数,将j初始化为(M – 1)以指向数组arr2[]的最后一个元素。
  • 使用变量i遍历数组arr1[]并执行以下步骤:
    • 检查sum1是否小于或等于sum2 ,然后将当前元素arr[i]与元素arr2[j]交换以最大化sum1
    • 交换后,更新sum1sum2的值,并递减j以指向倒数第二个元素并递增count
  • 完成上述步骤后,打印count的值作为所需的最小交换次数。

下面是上述方法的实现:

C++
// C++ program for the above approach
 
#include 
using namespace std;
 
// Function to find the minimum count
// of swaps required between the two
// arrays to makee the sum of arr1[]
// greater than that of arr2[]
int maximumCount(int arr1[], int arr2[],
                 int s1, int s2)
{
    // Stores the sum of the two arrays
    int sum1 = 0, sum2 = 0;
 
    // Calculate sum of arr1[]
    for (int i = 0; i < s1; i++) {
        sum1 += arr1[i];
    }
 
    // Calculate sum of arr2[]
    for (int j = 0; j < s2; j++) {
        sum2 += arr2[j];
    }
 
    int len = 0;
    if (s1 >= s2) {
        len = s2;
    }
    else {
        len = s1;
    }
 
    // Sort the arrays arr1[] and arr2[]
    sort(arr1, arr1 + s1);
    sort(arr2, arr2 + s2);
 
    int j = 0, k = s2 - 1, count = 0;
 
    // Traverse the array arr[]
    for (int i = 0; i < len; i++) {
 
        // If the sum1 is less than
        // or equal to sum2
        if (sum1 <= sum2) {
 
            // Swapping the elements
            if (arr2[k] >= arr1[i]) {
 
                // Update the sum1 and sum2
                int dif1 = arr1[j], dif2 = arr2[k];
                sum1 -= dif1;
                sum1 += dif2;
 
                sum2 -= dif2;
                sum2 += dif1;
                j++;
                k--;
 
                // Increment the count
                count++;
            }
            else {
                break;
            }
        }
        else {
            break;
        }
    }
 
    // Return the final count
    return count;
}
 
// Driver Code
int main()
{
    int arr1[] = { 1, 3, 2, 4 };
    int arr2[] = { 6, 7, 8 };
    int N = sizeof(arr1) / sizeof(arr1[0]);
    int M = sizeof(arr2) / sizeof(arr2[0]);
 
    // Function Call
    cout << maximumCount(arr1, arr2, N, M);
 
    return 0;
}


Java
// Java program for the above approach
import java.io.*;
import java.util.*;
class GFG
{
 
  // Function to find the minimum count
  // of swaps required between the two
  // arrays to makee the sum of arr1[]
  // greater than that of arr2[]
  static int maximumCount(int[] arr1, int[] arr2, int s1,
                          int s2)
  {
 
    // Stores the sum of the two arrays
    int sum1 = 0, sum2 = 0;
 
    // Calculate sum of arr1[]
    for (int i = 0; i < s1; i++)
    {
      sum1 += arr1[i];
    }
 
    // Calculate sum of arr2[]
    for (int j = 0; j < s2; j++)
    {
      sum2 += arr2[j];
    }
 
    int len = 0;
    if (s1 >= s2)
    {
      len = s2;
    }
    else
    {
      len = s1;
    }
 
    // Sort the arrays arr1[] and arr2[]
    Arrays.sort(arr1);
    Arrays.sort(arr2);
 
    int j = 0, k = s2 - 1, count = 0;
 
    // Traverse the array arr[]
    for (int i = 0; i < len; i++)
    {
 
      // If the sum1 is less than
      // or equal to sum2
      if (sum1 <= sum2)
      {
 
        // Swapping the elements
        if (arr2[k] >= arr1[i])
        {
 
          // Update the sum1 and sum2
          int dif1 = arr1[j], dif2 = arr2[k];
          sum1 -= dif1;
          sum1 += dif2;
 
          sum2 -= dif2;
          sum2 += dif1;
          j++;
          k--;
 
          // Increment the count
          count++;
        }
        else
        {
          break;
        }
      }
      else
      {
        break;
      }
    }
 
    // Return the final count
    return count;
  }
 
  // Driver Code
  public static void main(String[] args)
  {
 
    int[] arr1 = new int[] { 1, 3, 2, 4 };
    int[] arr2 = new int[] { 6, 7, 8 };
    int N = arr1.length;
    int M = arr2.length;
 
    // Function Call
    System.out.println(maximumCount(arr1, arr2, N, M));
  }
}
 
// This code is contributed by dharanendralv23


Python3
# Python3 program to implement
# the above approach
 
# Function to find the minimum count
# of swaps required between the two
# arrays to makee the sum of arr1[]
# greater than that of arr2[]
def maximumCount(arr1, arr2, s1, s2) :
                      
    # Stores the sum of the two arrays
    sum1 = 0
    sum2 = 0
 
    # Calculate sum of arr1[]
    for i in range(s1):
        sum1 += arr1[i]
 
    # Calculate sum of arr2[]
    for j in range(s2):
        sum2 += arr2[j]
 
    len = 0
    if (s1 >= s2) :
        lenn = s2  
    else :
        lenn = s1
 
    # Sort the arrays arr1[] and arr2[]
    arr1.sort();
    arr2.sort();
    j = 0
    k = s2 - 1
    count = 0
 
    # Traverse the array arr[]
    for i in range(lenn):
 
        # If the sum1 is less than
        # or equal to sum2
        if (sum1 <= sum2) :
 
            # Swapping the elements
            if (arr2[k] >= arr1[i]) :
 
                # Update the sum1 and sum2
                dif1 = arr1[j]
                dif2 = arr2[k]
                sum1 -= dif1
                sum1 += dif2
                sum2 -= dif2
                sum2 += dif1
                j += 1
                k -= 1
 
                # Increment the count
                count += 1           
            else :
                break          
        else :
            break
 
    # Return the final count
    return count
 
# Driver Code
 
arr1 = [ 1, 3, 2, 4 ]
arr2 = [ 6, 7, 8 ]
N = len(arr1)
M = len(arr2)
 
# Function Call
print(maximumCount(arr1, arr2, N, M))
 
# This code is contributed by sanjoy_62


C#
// C# program for the above approach
using System;
class GFG {
 
  // Function to find the minimum count
  // of swaps required between the two
  // arrays to makee the sum of arr1[]
  // greater than that of arr2[]
  static int maximumCount(int[] arr1, int[] arr2, int s1,
                          int s2)
  {
    // Stores the sum of the two arrays
    int sum1 = 0, sum2 = 0;
 
    // Calculate sum of arr1[]
    for (int i = 0; i < s1; i++) {
      sum1 += arr1[i];
    }
 
    // Calculate sum of arr2[]
    for (int a = 0; a < s2; a++) {
      sum2 += arr2[a];
    }
 
    int len = 0;
    if (s1 >= s2) {
      len = s2;
    }
    else {
      len = s1;
    }
 
    // Sort the arrays arr1[] and arr2[]
    Array.Sort(arr1);
    Array.Sort(arr2);
 
    int j = 0, k = s2 - 1, count = 0;
 
    // Traverse the array arr[]
    for (int i = 0; i < len; i++) {
 
      // If the sum1 is less than
      // or equal to sum2
      if (sum1 <= sum2) {
 
        // Swapping the elements
        if (arr2[k] >= arr1[i]) {
 
          // Update the sum1 and sum2
          int dif1 = arr1[j], dif2 = arr2[k];
          sum1 -= dif1;
          sum1 += dif2;
 
          sum2 -= dif2;
          sum2 += dif1;
          j++;
          k--;
 
          // Increment the count
          count++;
        }
        else {
          break;
        }
      }
      else {
        break;
      }
    }
 
    // Return the final count
    return count;
  }
 
  // Driver Code
  static public void Main()
  {
 
    int[] arr1 = new int[] { 1, 3, 2, 4 };
    int[] arr2 = new int[] { 6, 7, 8 };
    int N = arr1.Length;
    int M = arr2.Length;
 
    // Function Call
    Console.WriteLine(maximumCount(arr1, arr2, N, M));
  }
}
 
// This code is contributed by dharanendralv23


Javascript


输出:

1

时间复杂度: O(N*log N + M*log M)
辅助空间: O(1)

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