Max Sum Plus Plus

Time Limit: 2000/1000 MS (Java/Others)    Memory Limit: 65536/32768 K (Java/Others)
Total Submission(s): 25639    Accepted Submission(s): 8884

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. ^_^

 
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.
 
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
8

Hint

Huge input, scanf and dynamic programming is recommended.

 
Author
JGShining(极光炫影)
 
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#include<iostream>
#include<stdio.h>
#include<string>
#include<cstring>
using namespace std;
const int maxn = ;
int dp[maxn];
int pri[maxn];
int a[maxn]; int main()
{
int n,m;
while(~scanf("%d%d",&m,&n))
{
for(int i=;i<=n;i++) scanf("%d",a+i);
int tmp_max=-0x3fff;
dp[]=;
//pri[0]=0;
memset(pri,,sizeof(pri));
for(int i=;i<=m;i++)
{
tmp_max=-0x3fffffff;
for(int j=i;j<=n;j++)
{
dp[j]=max(dp[j-],pri[j-])+a[j];
pri[j-]=tmp_max;
if(tmp_max<dp[j]) tmp_max=dp[j];
} }
printf("%d\n",tmp_max);
}
return ;
}

设输入的数组为a[1...n],从中找出m个段,使者几个段的和为最大

dp[i][j]表示前j个数中取i个段的和的最大值,其中最后一个段包含a[j]。(这很关键)

则状态转移方程为:

dp[i][j]=max{dp[i][j-1]+a[j],max{dp[i-1][t]}+a[j]}    i-1=<t<j-1

因为dp[i][j]中a[j]可能就自身一个数组成最后一段,或者a[j]与a[j-1]等前面的数组成最后一段。

此题n数据太大,二维数组开不下,而且三重循环,想到状态转移方程后还是困难重重。

想想,二维数组不行的话,肯定要压缩成一维数组:

因为dp[i-1][t]的值只在计算dp[i][j]的时候用到,那么没有必要保存所有的dp[i][j] for i=1 to m,这样我们可以用一维数组存储。

用pre[j]表示j之前一个状态dp[i-1][]中1-j之间,不一定包含a[j]的最大字段和,然后推dp[i][j]状态时,dp[i][j]=max{pre[j-1],dp[j-1]}+a[j];

褐色的为了方便理解,其实不存在。

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