【DP】Codeforces1025D Recovering BST

题意:

给出n个点,每个点有一个点权 ai a i
现在要求构造一颗二叉搜索树,需要满足:每条边两端的点其权值不互质。
询问能否满足


分析:

很水的区间DP题啦。。。
不知道为什么同学们还有WK大佬都没做出来呢。。。
看来同学们的DP训练还得再做做啊。。。

(话是这么说,不过我似乎除了DP啥也不会了。。。好菜啊。。。)

首先,由于其是一颗二叉搜索树,所以其中序遍历必然是不下降的。

所以呢,可以将序列中连续的某一段当做一颗子树来处理:
每次枚举一个根节点,将原序列分为左右两个序列(即左子树和右子树)。

然后发现,对任意一个区间 (l,r) ( l , r ) 来说,其上一层的父亲节点必然是 l1 l − 1 r+1 r + 1 (cch和wk大佬都是这里被卡了呢)。

证明很显然啦。。。如果其父亲不是 l1 l − 1 r+1 r + 1 的话。。。你打算把中间空着的那一段放哪?

如果还没懂的话我再扯详细一点:
根据DP转移方式,每次在区间中枚举一个点后,将区间分为左半部分和右半部分两个子区间,那么这两个子区间的父亲节点即为我们枚举出来的这个点,所以这两个区间就满足上述条件,对其子序列数学归纳一下就证明出来了。

所以dp定义就很显然啦。。。
dp(i,j,0) d p ( i , j , 0 ) 表示区间 [l,r] [ l , r ] 构成的子树是否有一种方案满足其根节点的值与 al1 a l − 1 不互质
dp(i,j,1) d p ( i , j , 1 ) 表示区间 [l,r] [ l , r ] 构成的子树是否有一种方案满足其根节点的值与 ar+1 a r + 1 不互质

转移就是枚举一个k (lkr) ( l ≤ k ≤ r )
如果 dp[l][k1]=1 d p [ l ] [ k − 1 ] = 1 dp[k+1][r]=1 d p [ k + 1 ] [ r ] = 1 gcd(ak,al1) g c d ( a k , a l − 1 ) ,则 dp[l][r][0]=1 d p [ l ] [ r ] [ 0 ] = 1 ;
如果 dp[l][k1]=1 d p [ l ] [ k − 1 ] = 1 dp[k+1][r]=1 d p [ k + 1 ] [ r ] = 1 gcd(ak,ar+1) g c d ( a k , a r + 1 ) ,则 dp[l][r][1]=1 d p [ l ] [ r ] [ 1 ] = 1

额。。为了不卡常需要预处理一下每两个数的gcd。。然后就做完了。。。

#include<cstdio>
#include<cstring>
#include<cmath>
#include<vector>
#define SF scanf
#define PF printf
#define MAXN 710
using namespace std;
int a[MAXN],n;
bool dp[MAXN][MAXN][2];
int g[MAXN][MAXN];
int gcd(int x,int y){
    if(y==0)
        return x;
    return gcd(y,x%y);
}
int main(){
    SF("%d",&n);
    for(int i=1;i<=n;i++)
        SF("%d",&a[i]);
    for(int i=1;i<=n;i++)
        for(int j=1;j<=n;j++)
            g[i][j]=gcd(a[i],a[j]);
    for(int len=1;len<=n;len++)
        for(int l=1;l+len-1<=n;l++){
            int r=l+len-1;
            for(int k=l;k<=r;k++)
                if((k==l||dp[l][k-1][1])&&(k==r||dp[k+1][r][0])){
                    if(l!=1&&g[k][l-1]!=1)
                        dp[l][r][0]=1;
                    if(r!=n&&g[k][r+1]!=1)
                        dp[l][r][1]=1;
                }
        }
    bool ans=0;
    for(int rt=1;rt<=n;rt++)
        if((rt==1||dp[1][rt-1][1])&&(rt==n||dp[rt+1][n][0]))
            ans=1;
    if(ans==0)
        PF("No\n");
    else
        PF("Yes\n");
}
### 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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