HDU-5077-NAND(DFS+打表)


Problem Description
Xiaoqiang entered the “shortest code” challenge organized by some self-claimed astrologists. He was given a boolean function taking n inputs (in C++):

bool f(bool x1, bool x2, bool x3){
//your code goes here
//return something
}


All possible inputs and expected outputs of this function have been revealed:



Xiaoqiang’s code must be like:

bool a = NAND(b, c);

where “a” is a newly defined variable,“b” and “c” can be a constant (0/1) or a function parameter (x1/x2/x3) or a previously defined variable. NAND is the “not-and” function:

NAND(b, c)=!(b&&c)

Because NAND is universal, Xiaoqiang knew that he could implement any boolean function he liked. Also, at the end of the code there should be a return statement:

return y;

where y can be a constant or a function parameter or a previously defined variable. After staring at the function for a while, Xiaoqiang came up with the answer:

bool a = NAND(x1, x2);
bool b = NAND(x2, x3);
bool y = NAND(a, b); return y;


Xiaoqiang wants to make sure that his solution is the shortest possible. Can you help him?
 

Input
The first line contains an integer T (T ≤ 20) denoting the number of the test cases.

For each test case, there is one line containing 8 characters encoding the truth table of the function.
 

Output
For each test case, output a single line containing the minimum number of lines Xiaoqiang has to write.
 

Sample Input
  
1 00010011
 

Sample Output
  
4
Hint
Due to the small input domain, you can solve all the cases on your computer and submit a program with a table of all the answers.
 

Source
 

思路:暴搜打表。 DFS的时候注意剪枝,递归的时候把i和j往下传,这是一个很有效的剪枝。


#include <stdio.h>
#define max(A,B)(A>B?A:B)

int num[1<<8],ans[1<<8],zh[256][256],cnt;
bool vis[1<<8];

void dfs(int dep,int x,int y)
{
    int i,j;

    if(ans[num[cnt-1]]>dep) ans[num[cnt-1]]=dep;

    if(dep==10)  return;

    for(i=x;i<cnt;i++)
    {
        for(j=(i==x?y:0);j<=i;j++)//这里是关键
        {
            if(!vis[zh[num[i]][num[j]]])
            {
                vis[zh[num[i]][num[j]]]=1;
                num[cnt++]=zh[num[i]][num[j]];

                dfs(dep+1,i,j);

                vis[zh[num[i]][num[j]]]=0;
                cnt--;
            }
        }
    }
}

int main()
{
    int i,j;

    num[0]=240;//00001111
    num[1]=204;//00110011
    num[2]=170;//01010101
    num[3]=0;//00000000
    num[4]=255;//11111111

    for(i=0;i<(1<<8);i++) ans[i]=11;

    vis[240]=vis[204]=vis[170]=vis[0]=vis[255]=1;
    ans[240]=ans[204]=ans[170]=ans[0]=ans[255]=1;

    for(i=0;i<256;i++) for(j=0;j<256;j++)
    {
        zh[i][j]=~(i&j);
        zh[i][j]&=0x000000FF;
    }

    cnt=5;

    dfs(1,0,0);

    for(i=0;i<(1<<8);i++)  printf("%d,",ans[i]);
}

### 关于HDU - 6609 的题目解析 由于当前未提供具体关于 HDU - 6609 题目的详细描述,以下是基于一般算法竞赛题型可能涉及的内容进行推测和解答。 #### 可能的题目背景 假设该题目属于动态规划类问题(类似于多重背包问题),其核心在于优化资源分配或路径选择。此类问题通常会给出一组物品及其属性(如重量、价值等)以及约束条件(如容量限制)。目标是最优地选取某些物品使得满足特定的目标函数[^2]。 #### 动态转移方程设计 如果此题确实是一个变种的背包问题,则可以采用如下状态定义方法: 设 `dp[i][j]` 表示前 i 种物品,在某种条件下达到 j 值时的最大收益或者最小代价。对于每一种新加入考虑范围内的物体 k ,更新规则可能是这样的形式: ```python for i in range(n): for s in range(V, w[k]-1, -1): dp[s] = max(dp[s], dp[s-w[k]] + v[k]) ``` 这里需要注意边界情况处理以及初始化设置合理值来保证计算准确性。 另外还有一种可能性就是它涉及到组合数学方面知识或者是图论最短路等相关知识点。如果是后者的话那么就需要构建相应的邻接表表示图形结构并通过Dijkstra/Bellman-Ford/Floyd-Warshall等经典算法求解两点间距离等问题了[^4]。 最后按照输出格式要求打印结果字符串"Case #X: Y"[^3]。 #### 示例代码片段 下面展示了一个简单的伪代码框架用于解决上述提到类型的DP问题: ```python def solve(): t=int(input()) res=[] cas=1 while(t>0): n,k=list(map(int,input().split())) # Initialize your data structures here ans=find_min_unhappiness() # Implement function find_min_unhappiness() res.append(f'Case #{cas}: {round(ans)}') cas+=1 t-=1 print("\n".join(res)) solve() ```
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