Game HDU - 3657(还是算最小割吧)

本文介绍了一种基于网格的游戏算法,玩家从网格中取出数值以获得最高得分。文章详细解释了游戏规则,并提供了一个C++代码示例,利用图算法求解最大流问题来找出最优解。

onmylove has invented a game on n × m grids. There is one positive integer on each grid. Now you can take the numbers from the grids to make your final score as high as possible. The way to get score is like
the following:
● At the beginning, the score is 0;
● If you take a number which equals to x, the score increase x;
● If there appears two neighboring empty grids after you taken the number, then the score should be decreased by 2(x&y). Here x and y are the values used to existed on these two grids. Please pay attention that “neighboring grids” means there exits and only exits one common border between these two grids.

Since onmylove thinks this problem is too easy, he adds one more rule:
● Before you start the game, you are given some positions and the numbers on these positions must be taken away.
Can you help onmylove to calculate: what’s the highest score onmylove can get in the game?
Input
Multiple input cases. For each case, there are three integers n, m, k in a line.
n and m describing the size of the grids is n ×m. k means there are k positions of which you must take their numbers. Then following n lines, each contains m numbers, representing the numbers on the n×m grids.Then k lines follow. Each line contains two integers, representing the row and column of one position
and you must take the number on this position. Also, the rows and columns are counted start from 1.
Limits: 1 ≤ n, m ≤ 50, 0 ≤ k ≤ n × m, the integer in every gird is not more than 1000.
Output
For each test case, output the highest score on one line.
Sample Input
2 2 1
2 2
2 2
1 1
2 2 1
2 7
4 1
1 1
Sample Output
4
9

Hint
As to the second case in Sample Input, onmylove gan get the highest score when calulating like this:
2 + 7 + 4 - 2 × (2&4) - 2 × (2&7) = 13 - 2 × 0 - 2 × 2 = 9.

上一题的加强版~~~
这题不能用最大独立点权来理解,而是用最小割来理解这个题比较好

#include<iostream>
#include<cstdio>
#include<cmath>
#include<cstring>
#include<queue>
#define INF 0x3f3f3f3f
using namespace std;
const int maxn=2505;
const int maxx=20005;
int edge;
int to[maxx],flow[maxx],nex[maxx];
int head[maxn];

void addEdge(int v,int u,int cap)
{
    to[edge]=u,flow[edge]=cap,nex[edge]=head[v],head[v]=edge++;
    to[edge]=v,flow[edge]=0,nex[edge]=head[u],head[u]=edge++;
}
int vis[maxn];
int pre[maxn];
bool bfs(int s,int e)
{
    queue<int> que;
    pre[s]=-1;
    memset(vis,-1,sizeof(vis));
    que.push(s);
    vis[s]=0;
    while(!que.empty())
    {
        int u=que.front();
        que.pop();
        for(int i=head[u];~i;i=nex[i])
        {
            int v=to[i];
            if(vis[v]==-1&&flow[i])
            {
                vis[v]=vis[u]+1;
                if(v==e)
                    return true;
                que.push(v);
            }

        }
    }
    return false;
}
int dfs(int s,int t,int f)
{
    if(s==t||!f)
        return f;
    int r=0;
    for(int i=head[s];~i;i=nex[i])
    {
        int v=to[i];
        if(vis[v]==vis[s]+1&&flow[i])
        {
            int d=dfs(v,t,min(f,flow[i]));
            if(d>0)
            {
                flow[i]-=d;
                flow[i^1]+=d;
                r+=d;
                f-=d;
                if(!f)
                    break;
            }
        }
    }
    if(!r)
        vis[s]=INF;
    return r;
}
int maxFlow(int s ,int e)//然后直接调用这个即可
{
    int ans=0;
    while(bfs(s,e))
        ans+=dfs(s,e,INF);
    return ans;
}

void init()//记得每次使用前初始化
{
    memset(head,-1,sizeof(head));
    edge=0;
}
int b[][2]={{0,1},{0,-1},{1,0},{-1,0}};
int a[55][55];
bool flag[55][55];
int main()
{
    int n,m,k;
    int x,y;
    while(scanf("%d%d%d",&n,&m,&k)==3)
    {
        int total=0;
        memset(flag,0,sizeof(flag));
        init();
        for(int i=1;i<=n;i++)
            for(int j=1;j<=m;j++)
                scanf("%d",&a[i][j]),total+=a[i][j];
        while(k--)
        {
            scanf("%d%d",&x,&y);
            flag[x][y]=true;
        }
        for(int i=1;i<=n;i++)
            for(int j=1;j<=m;j++)
        {
            if((i+j)&1)
            {
                addEdge(0,(i-1)*m+j,flag[i][j]==0?a[i][j]:INF);
                for(int k=0;k<4;k++)
                {
                    int xx=i+b[k][0];
                    int yy=j+b[k][1];
                    if(xx<1||xx>n||yy<1||yy>m)
                        continue;
                    addEdge((i-1)*m+j,(xx-1)*m+yy,2*(a[i][j]&a[xx][yy]));
                }
            }
            else
                addEdge((i-1)*m+j,n*m+1,flag[i][j]==0?a[i][j]:INF);
        }
        printf("%d\n",total-maxFlow(0,n*m+1));
    }
    return 0;
}
HDU-3480 是一个典型的动态规划问题,其题目标题通常为 *Division*,主要涉及二维费用背包问题或优化后的动态规划策略。题目大意是:给定一个整数数组,将其划分为若干个连续的子集,每个子集最多包含 $ m $ 个元素,并且每个子集的最大值与最小值之差不能超过给定的阈值 $ t $,目标是使所有子集的划分代价总和最小。每个子集的代价是该子集最大值与最小值的差值。 ### 动态规划思路 设 $ dp[i] $ 表示前 $ i $ 个元素的最小代价。状态转移方程如下: $$ dp[i] = \min_{j=0}^{i-1} \left( dp[j] + cost(j+1, i) \right) $$ 其中 $ cost(j+1, i) $ 表示从第 $ j+1 $ 到第 $ i $ 个元素构成一个子集的代价,即 $ \max(a[j+1..i]) - \min(a[j+1..i]) $。 为了高效计 $ cost(j+1, i) $,可以使用滑动窗口或单调队列等数据结构来维护区间最大值与最小值,从而将时间复杂度优化到可接受的范围。 ### 示例代码 以下是一个简化版本的动态规划实现,使用暴力方式计区间代价,适用于理解问题结构: ```cpp #include <bits/stdc++.h> using namespace std; const int INF = 0x3f3f3f3f; const int MAXN = 10010; int a[MAXN]; int dp[MAXN]; int main() { int T, n, m; cin >> T; for (int Case = 1; Case <= T; ++Case) { cin >> n >> m; for (int i = 1; i <= n; ++i) cin >> a[i]; dp[0] = 0; for (int i = 1; i <= n; ++i) { dp[i] = INF; int mn = a[i], mx = a[i]; for (int j = i; j >= max(1, i - m + 1); --j) { mn = min(mn, a[j]); mx = max(mx, a[j]); if (mx - mn <= T) { dp[i] = min(dp[i], dp[j - 1] + mx - mn); } } } cout << "Case " << Case << ": " << dp[n] << endl; } return 0; } ``` ### 优化策略 - **单调队列**:可以使用两个单调队列分别维护当前窗口的最大值与最小值,从而将区间代价计的时间复杂度从 $ O(n^2) $ 降低到 $ O(n) $。 - **斜率优化**:若问题满足特定的决策单调性,可以考虑使用斜率优化技巧进一步加速状态转移过程。 ### 时间复杂度分析 原始暴力解法的时间复杂度为 $ O(n^2) $,在 $ n \leq 10^4 $ 的情况下可能勉强通过。通过单调队列优化后,可以稳定运行于 $ O(n) $ 或 $ O(n \log n) $。 ### 应用场景 HDU-3480 的问题模型可以应用于资源调度、任务划分等场景,尤其适用于需要控制子集内部差异的问题,如图像分块压缩、数据分段处理等[^1]。 ---
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