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📜  圆形数组中的最大和,使得没有两个元素相邻 | 2套

📅  最后修改于: 2021-09-05 11:36:14             🧑  作者: Mango

给定一个由正数组成的数组 arr[] ,找到一个子序列的最大和,约束条件是序列中没有 2 个数字应该在数组中相邻,其中假设最后一个元素和第一个元素相邻。
例子:

方法:思路是使用Memorization算法来解决上面提到的问题。最重要的观察是第一个和最后一个元素永远不能一起选择。所以,我们可以把问题分成两部分:

  • 我们可以从索引0 到数组大小的最大总和– 2
  • 我们可以从索引1 到数组大小得到的最大总和– 1

答案将是这两个和的最大值,可以使用Dynamic Programming解决。
下面是上述方法的实现:

C++
// C++ program to find maximum sum
// in circular array such that
// no two elements are adjacent
 
#include 
using namespace std;
 
// Store the maximum possible at each index
vector dp;
 
int maxSum(int i, vector& subarr)
{
 
    // When i exceeds the index of the
    // last element simply return 0
    if (i >= subarr.size())
        return 0;
 
    // If the value has already been calculated,
    // directly return it from the dp array
    if (dp[i] != -1)
        return dp[i];
 
    // The next states are don't take
    // this element and go to (i + 1)th state
    // else take this element
    // and go to (i + 2)th state
    return dp[i]
           = max(maxSum(i + 1, subarr),
                 subarr[i]
                     + maxSum(i + 2, subarr));
}
 
// function to find the max value
int Func(vector arr)
{
    vector subarr = arr;
 
    // subarr contains elements
    // from 0 to arr.size() - 2
    subarr.pop_back();
 
    // Initializing all the values with -1
    dp.resize(subarr.size(), -1);
 
    // Calculating maximum possible
    // sum for first case
    int max1 = maxSum(0, subarr);
 
    subarr = arr;
 
    // subarr contains elements
    // from 1 to arr.size() - 1
    subarr.erase(subarr.begin());
 
    dp.clear();
 
    // Re-initializing all values with -1
    dp.resize(subarr.size(), -1);
 
    // Calculating maximum possible
    // sum for second case
    int max2 = maxSum(0, subarr);
 
    // Printing the maximum between them
    cout << max(max1, max2) << endl;
}
 
// Driver code
int main()
{
 
    vector arr = { 1, 2, 3, 1 };
 
    Func(arr);
 
    return 0;
}


Java
// Java program to find maximum sum
// in circular array such that
// no two elements are adjacent
import java.util.*;
class GFG{
 
// Store the maximum
// possible at each index
static Vector dp =
              new Vector<>();
 
static int maxSum(int i,
                  Vector subarr)
{
  // When i exceeds the index of the
  // last element simply return 0
  if (i >= subarr.size())
    return 0;
 
  // If the value has already
  // been calculated, directly
  // return it from the dp array
  if (dp.get(i) != -1)
    return dp.get(i);
 
  // The next states are don't take
  // this element and go to (i + 1)th state
  // else take this element
  // and go to (i + 2)th state
  dp.add(i, Math.max(maxSum(i + 1, subarr),
                     subarr.get(i) +
                     maxSum(i + 2, subarr)));
  return dp.get(i);
}
 
// function to find the max value
static void Func(Vector arr)
{
  Vector subarr =
         new Vector<>();
  subarr.addAll(arr);
 
  // subarr contains elements
  // from 0 to arr.size() - 2
  subarr.remove(subarr.size() - 1);
 
  // Initializing all the values with -1
  dp.setSize(subarr.size());
  Collections.fill(dp, -1);
 
  // Calculating maximum possible
  // sum for first case
  int max1 = maxSum(0, subarr);
 
  subarr = arr;
 
  // subarr contains elements
  // from 1 to arr.size() - 1
  subarr.remove(0);
 
  dp.clear();
 
  // Re-initializing all values with -1
  dp.setSize(subarr.size());
  Collections.fill(dp, -1);
 
 
  // Calculating maximum possible
  // sum for second case
  int max2 = maxSum(0, subarr);
 
  // Printing the maximum between them
  System.out.print(Math.max(max1, max2) + "\n");
}
 
// Driver code
public static void main(String[] args)
{
  Vector arr =new Vector<>();
  arr.add(1);
  arr.add(2);
  arr.add(3);
  arr.add(1);
  Func(arr);
}
 
// This code is contributed by gauravrajput1


Python3
# Python3 program to find maximum sum
# in circular array such that
# no two elements are adjacent
 
# Store the maximum possible at each index
dp = []
 
def maxSum(i, subarr):
 
    # When i exceeds the index of the
    # last element simply return 0
    if (i >= len(subarr)):
        return 0
 
    # If the value has already been
    # calculated, directly return
    # it from the dp array
    if (dp[i] != -1):
        return dp[i]
 
    # The next states are don't take
    # this element and go to (i + 1)th state
    # else take this element
    # and go to (i + 2)th state
    dp[i] = max(maxSum(i + 1, subarr),
                subarr[i] +
                maxSum(i + 2, subarr))
    return dp[i]
 
# function to find the max value
def Func(arr):
    subarr = arr
 
    # subarr contains elements
    # from 0 to arr.size() - 2
    subarr.pop()
    global dp
     
    # Initializing all the values with -1
    dp= [-1] * (len(subarr))
 
    # Calculating maximum possible
    # sum for first case
    max1 = maxSum(0, subarr)
 
    subarr = arr
 
    # subarr contains elements
    # from 1 to arr.size() - 1
    subarr = subarr[:]
 
    del dp
 
    # Re-initializing all values with -1
    dp = [-1] * (len(subarr))
 
    # Calculating maximum possible
    # sum for second case
    max2 = maxSum(0, subarr)
 
    # Printing the maximum between them
    print(max(max1, max2))
 
# Driver code
if __name__ == "__main__":
    arr = [1, 2, 3, 1]
    Func(arr)
     
# This code is contributed by Chitranayal


Javascript


输出:

4

时间复杂度: O(N)
辅助空间复杂度: O(N)
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