hdu 1081To The Max(二维最大连续子串和)

2014-11-24 08:09:05 · 作者: · 浏览: 0

To The Max

Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 65536/32768 K (Java/Others)
Total Submission(s): 6994 Accepted Submission(s): 3375


Problem Description Given a two-dimensional array of positive and negative integers, a sub-rectangle is any contiguous sub-array of size 1 x 1 or greater located within the whole array. The sum of a rectangle is the sum of all the elements in that rectangle. In this problem the sub-rectangle with the largest sum is referred to as the maximal sub-rectangle.

As an example, the maximal sub-rectangle of the array:

0 -2 -7 0
9 2 -6 2
-4 1 -4 1
-1 8 0 -2

is in the lower left corner:

9 2
-4 1
-1 8

and has a sum of 15.

Input The input consists of an N x N array of integers. The input begins with a single positive integer N on a line by itself, indicating the size of the square two-dimensional array. This is followed by N 2 integers separated by whitespace (spaces and newlines). These are the N 2 integers of the array, presented in row-major order. That is, all numbers in the first row, left to right, then all numbers in the second row, left to right, etc. N may be as large as 100. The numbers in the array will be in the range [-127,127].

Output Output the sum of the maximal sub-rectangle.

Sample Input
4
0 -2 -7 0 9 2 -6 2
-4 1 -4 1 -1
8 0 -2

Sample Output
15


题目大意:给你一个n*n的矩阵,让你找一个子矩阵,使得这个矩阵内所有数字的和最大。
解题思路:先联系一维的最大连续子串和,dp[i]=max(dp[i-1],0)+a[i]其中dp[i]表示前面i项内所取得的最大值,必须包含第i项。a[i]表示第i项。这个二维矩阵的题目也可以进行转换。先用mp[i][j],表示第i行前j列的和。那么状态转移方程可以转换为dp[k]=max(dp[k-1],0)+a[k],我们可以将a[k]看作第j列到第i列的第k项的和,a[k]=mp[k][i]-mp[k][j-1].
题目地址:To The Max
AC代码:
#include
  
   
#include
   
     #include
    
      #include
     
       using namespace std; int mp[105][105]; int main() { int i,j,k,res,n,x; while(cin>>n) { res=-1e9; memset(mp,0,sizeof(mp)); for(i=1;i<=n;i++) for(j=1;j<=n;j++) { scanf("%d",&x); mp[i][j]=mp[i][j-1]+x; } for(i=1;i<=n;i++) { for(j=1;j<=i;j++) //从第j列到第i列 { int tmp=-1; for(k=1;k<=n;k++) //看成一维的 dp[k]=max(dp[k-1],0)+a[k] { tmp=max(tmp,0)+mp[k][i]-mp[k][j-1]; res=max(res,tmp); } } } cout<