Codeforces 293E Close Vertices

本文提供Codeforces293E题目的详细解答,采用枚举链权值的方法结合树状数组来求解路径问题。通过排序和枚举策略优化算法效率。

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Close Vertices

Codeforces 293E
求路径,你懂的点分它

1.权值可能会很大,但是l小于等于n。所以可以考虑枚举链的权值,查询长度

2.存下链的长度和权值和,按权值排序。从大到小枚举,从小到大往BIT里塞长度,当A[i].val+A[j].val<=w时把A[j]塞入BIT。即在BIT的A[j].l处。

具体代码如下:

#include<bits/stdc++.h>
using namespace std;
const int M=1e5+5;
int n,W,LL;
int head[M],asdf;
long long ans;
struct edge {
    int to,cost,nxt;
} G[M*2];
void add_edge(int a,int b,int c) {
    G[++asdf].to=b;
    G[asdf].nxt=head[a];
    G[asdf].cost=c;
    head[a]=asdf;
}
struct BIT {
    int sum[M];
    void add(int x,int a) {
        while(x<=n) {
            sum[x]+=a;
            x+=-x&x;
        }
    }
    int query(int x) {
        int tot=0;
        while(x>0) {
            tot+=sum[x];
            x-=-x&x;
        }
        return tot;
    }
} BIT;
bool mark[M];
int que[M],sz[M],son[M],que_len;
void get_root(int x,int f) {
    que[++que_len]=x;
    sz[x]=1;
    son[x]=0;
    for(int i=head[x]; i; i=G[i].nxt) {
        int y=G[i].to;
        if(y==f||mark[y])continue;
        get_root(y,x);
        sz[x]+=sz[y];
        son[x]=max(son[x],sz[y]);
    }
}
int len;
struct node {
    int l,val;
    bool operator <(const node &tmp)const {
        return val<tmp.val;
    }
} dis[M];
void get_dis(int x,int f,int l,int val) {
    for(int i=head[x]; i; i=G[i].nxt) {
        int y=G[i].to;
        if(y==f||mark[y])continue;
        dis[++len]=(node) {
            l+1,val+G[i].cost
        };
        get_dis(y,x,l+1,val+G[i].cost);
    }
}
void calc(int t) {
    sort(dis+1,dis+1+len);//从小到大
    int l1=1;
    long long sum=0;
    for(int i=len; i>=1; i--) { //从大到小枚举边
        if(t>0) {
            if(dis[i].l<=LL&&dis[i].val<=W)ans++;
        }
        if(dis[i].val+dis[i].val<=W&&dis[i].l+dis[i].l<=LL)sum--;
        while(l1<=len&&dis[l1].val+dis[i].val<=W) {
            BIT.add(dis[l1].l,1);//从小到大加边
            l1++;
        }
        sum+=BIT.query(LL-dis[i].l);
    }
    ans+=t*sum/2;
    while(l1-1>0) {
        l1--;
        BIT.add(dis[l1].l,-1);
    }
}
void solve(int x) {
    que_len=0;
    get_root(x,x);
    for(int i=1; i<=que_len; i++) {
        son[que[i]]=max(son[que[i]],que_len-sz[que[i]]);
        if(son[que[i]]<son[x])x=que[i];
    }
    mark[x]=1;
    len=0;
    get_dis(x,x,0,0);
    calc(1);
    for(int i=head[x]; i; i=G[i].nxt) {
        int y=G[i].to;
        if(mark[y])continue;
        len=0;
        dis[++len]=(node) {
            1,G[i].cost
        };
        get_dis(y,x,1,G[i].cost);
        calc(-1);
        solve(y);
    }
}
int main() {
    scanf("%d %d %d",&n,&LL,&W);
    int a,c;
    for(int i=2; i<=n; i++) {
        scanf("%d %d",&a,&c);
        add_edge(a,i,c);
        add_edge(i,a,c);
    }
    solve(1);
    printf("%I64d\n",ans);
    return 0;
}
### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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