http://poj.org/problem?id=1050
Description
Given a two-dimensional array of positive and negative integers, a sub-rectangle is any contiguous sub-array of size 1*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 * 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
150
代码:
#include <iostream> #include <stdio.h> #include <math.h> #include <algorithm> using namespace std; const int maxn = 110; int N; int mp[maxn][maxn], sum[maxn][maxn]; int maxx = -1e5; int Maxnum(int l, int r) { int c[maxn], dp[maxn]; for(int i = 0; i < N; i ++) c[i] = sum[i][r] - sum[i][l - 1]; dp[0] = c[0]; int ans = max(ans, dp[0]); for(int i = 1; i < N; i ++) { dp[i] = max(dp[i - 1] + c[i], c[i]); ans = max(ans, dp[i]); } return ans; } int main() { scanf("%d", &N); for(int i = 0; i < N; i ++) { for(int j = 0; j < N; j ++) { scanf("%d", &mp[i][j]); } } for(int j = 0; j < N; j ++) { for(int i = 0; i < N; i ++) { if(i == 0) sum[j][i] = mp[i][j]; else sum[j][i] = sum[j][i - 1] + mp[i][j]; } } for(int i = 0; i < N; i ++) { for(int j = N - 1; j > i; j --) { maxx = max(maxx, Maxnum(i, j)); } } printf("%d\n", maxx); return 0; }
枚举上下边界然后枚举最大子序列的值 $O(N^3)$ 时间复杂度
FH