[Codeforces781D]Axel and Marston in Bitland(DP+bitset)

本文介绍了一种解决特定图论问题的算法,该问题涉及寻找一条从起点到终点的有效路径,路径长度为2的幂次。通过使用状态压缩和位操作技术,文章详细阐述了如何构建一个高效的解决方案。

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这里放传送门

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题解

可以发现这个串它有一些特点,首先它的长度是2的幂,并且它是一个正串接着一个反串那种类型,正串的开头肯定是1,反串的开头肯定是0。那么可以用 f[i][j][k][l] 表示当前是在递推以1开头的串还是0开头的串/长度为2的几次幂/起点是 k /终点是 l 的路径是否有可行方案。递推的话就是如果长度为 2j1 的正串可以从x跑到某个中间点k,长度为 2j1 的反串可以从k跑到y,那么就有长度为 2j 的合法路径从x跑到y。如果把第四维用bitset压起来的话转移就直接做位运算就可以了。
判断无解的话就是最后如果存在 260 的合法路径就就输出-1,否则就开始构造答案。构造答案的过程是从高位到低位贪心地依次判断这一位能不能加进去,就是开一个bitset表示前面更高的那些位弄完了以后哪些点是可行的终点,一开始只有1号点一个点是可行的。然后每一位的时候枚举所有的点,如果这个点是可行的终点说明这个点后面还能接上一段路。最后如果这一位存在可行方案就把这一位加进去。

代码

#include<bitset>
#include<cstdio>
#include<cstring>
#include<algorithm>
using namespace std;
const long long inf=1e18;
int n,m,now;
long long ans,bin[70];
bitset<510> f[2][63][510],g,tmp;
int main()
{
    scanf("%d%d",&n,&m);
    for (int i=1;i<=m;i++){
        int x,y,z;
        scanf("%d%d%d",&x,&y,&z);
        f[z][0][x][y]=1;//初值按照每一条边赋值
    }
    for (int i=1;i<=60;i++)
      for (int j=1;j<=n;j++)
        for (int k=1;k<=n;k++){
            if (f[0][i-1][j][k]!=0) f[0][i][j]|=f[1][i-1][k];
            if (f[1][i-1][j][k]!=0) f[1][i][j]|=f[0][i-1][k];
        }
    if (f[0][60][1].count()){
       printf("-1\n");return 0;
    }//先判断一下是否无解
    now=0;tmp[1]=1;bin[0]=1;
    for (int i=1;i<=60;i++) bin[i]=bin[i-1]*2;
    for (int i=60;i>=0;i--){
        g.reset();
        for (int j=1;j<=n;j++)
          if (tmp[j]) g|=f[now][i][j];
        if (g.count()!=0){//如果当前位可行就记录答案
            now^=1;tmp=g;ans|=bin[i];
        }
    }
    if (ans>inf) printf("-1\n");//注意输出的时候也要判断一下
    else printf("%I64d\n",ans);
    return 0;
}
### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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