HDU 1024 Max Sum Plus Plus
Max Sum Plus Plus
Time Limit: 2000/1000 MS (Java/Others) Memory Limit: 65536/32768 K (Java/Others)Total Submission(s): 21300 Accepted Submission(s): 7119
Problem Description
Now I think you have got an AC in Ignatius.L's "Max Sum" problem. To be a brave ACMer, we always challenge ourselves to more difficult problems. Now you are faced with a more difficult problem.
Given a consecutive number sequence S1, S2, S3, S4 ... Sx, ... Sn (1 ≤ x ≤ n ≤ 1,000,000, -32768 ≤ Sx ≤ 32767). We define a function sum(i, j) = Si + ... + Sj (1 ≤ i ≤ j ≤ n).
Now given an integer m (m > 0), your task is to find m pairs of i and j which make sum(i1, j1) + sum(i2, j2) + sum(i3, j3) + ... + sum(im, jm) maximal (ix ≤ iy ≤ jx or ix ≤ jy ≤ jx is not allowed).
But I`m lazy, I don't want to write a special-judge module, so you don't have to output m pairs of i and j, just output the maximal summation of sum(ix, jx)(1 ≤ x ≤ m) instead. ^_^
Given a consecutive number sequence S1, S2, S3, S4 ... Sx, ... Sn (1 ≤ x ≤ n ≤ 1,000,000, -32768 ≤ Sx ≤ 32767). We define a function sum(i, j) = Si + ... + Sj (1 ≤ i ≤ j ≤ n).
Now given an integer m (m > 0), your task is to find m pairs of i and j which make sum(i1, j1) + sum(i2, j2) + sum(i3, j3) + ... + sum(im, jm) maximal (ix ≤ iy ≤ jx or ix ≤ jy ≤ jx is not allowed).
But I`m lazy, I don't want to write a special-judge module, so you don't have to output m pairs of i and j, just output the maximal summation of sum(ix, jx)(1 ≤ x ≤ m) instead. ^_^
Input
Each test case will begin with two integers m and n, followed by n integers S1, S2, S3 ... Sn.
Process to the end of file.
Process to the end of file.
Output
Output the maximal summation described above in one line.
Sample Input
1 3 1 2 3 2 6 -1 4 -2 3 -2 3
Sample Output
6 8HintHuge input, scanf and dynamic programming is recommended.
对于这个题目,也是不太会做,看了半天题解。首先写出动态转移方程:
dp[i][j]=max(dp[i][j-1]+num[j],dp(i-1,t)+num[j]) 其中-- 未完整表达式 i - 1 <= t <= j - 1
这个比较好理解,就是将j个数分成i份,其中无非分成两种情况,第一种情况是前面与当前的连在一起,第二种情况即两段分开。我们只要找到dp[i][j - 1]和dp[i - 1][t]中的较大的一个加上当前j位置的数,就可以得到dp[i][j],所以我们需要一个数组pre_max[N],用pre_max[j - 1]来代表dp[i - 1][t]的最大值。我们将dp[i][t]的值一直存储,就存储在n的位置。然后再每次更新完当前的pre_max以后更新pre_max[n]位置的值。、
具体参考:http://www.cnblogs.com/dongsheng/archive/2013/05/28/3104629.html
代码如下:
/************************************************************************* > File Name: Max_Sum_Plus_Plus.cpp > Author: Zhanghaoran > Mail: chilumanxi@xiyoulinux.org > Created Time: Thu 22 Oct 2015 06:14:46 PM CST ************************************************************************/ #include <iostream> #include <algorithm> #include <cstring> #include <cstdio> #include <cstdlib> using namespace std; const int N = 1000010; int n, m; int a[N]; int pre_max[N]; int dp(int m, int n){ for(int i = 1; i <= m; i ++){ int temp = 0; for(int t = 1; t <= i; t ++) temp += a[t]; pre_max[n] = temp; for(int j = i + 1; j <= n; j ++){ temp = max(pre_max[j - 1], temp) + a[j]; pre_max[j - 1] = pre_max[n]; pre_max[n] = max(temp, pre_max[n]); } } return pre_max[n]; } int main(void){ while(~scanf("%d %d", &m, &n)){ memset(pre_max, 0, sizeof(pre_max)); for(int i = 1; i <= n; i ++){ scanf("%d", &a[i]); } cout << dp(m, n) << endl; } return 0; }