HDU-5723 Abandoned country

本文介绍了一道关于寻找最小生成树并计算其上任意两点间距离期望的算法问题。通过Kruskal算法求得最小生成树后,利用特定技巧计算了所有边对期望路径长度的贡献。

Problem Description
An abandoned country has  n(n100000)  villages which are numbered from 1 to  n . Since abandoned for a long time, the roads need to be re-built. There are  m(m1000000)  roads to be re-built, the length of each road is  wi(wi1000000) . Guaranteed that any two  wi  are different. The roads made all the villages connected directly or indirectly before destroyed. Every road will cost the same value of its length to rebuild. The king wants to use the minimum cost to make all the villages connected with each other directly or indirectly. After the roads are re-built, the king asks a men as messenger. The king will select any two different points as starting point or the destination with the same probability. Now the king asks you to tell him the minimum cost and the minimum expectations length the messenger will walk.
 

Input
The first line contains an integer  T(T10)  which indicates the number of test cases. 

For each test case, the first line contains two integers  n,m  indicate the number of villages and the number of roads to be re-built. Next  m  lines, each line have three number  i,j,wi , the length of a road connecting the village  i  and the village  j  is  wi .
 

Output
output the minimum cost and minimum Expectations with two decimal places. They separated by a space.
 

Sample Input
  
1 4 6 1 2 1 2 3 2 3 4 3 4 1 4 1 3 5 2 4 6
 

Sample Output
  
6 3.33
 

Author
HIT
 

Source

题目大意:

有n个点,有m条边,让你求它的最小生成树,并且在这个生成树上,求任意两点间的距离的期望。

解题思路:

第一问比较裸,就直接求最小生成树就好,第二问需要一些技巧。

现在有一条边ab,其中b的子树个数为num,那么这条边被经过的次数为(n - num) * num

然后乘一下这条边的权值就可以了

代码:

#include <cstdio>
#include <vector>
#include <cstring>
#include <algorithm>
using namespace std;

const int maxn = 1e5 + 5;

typedef long long LL;
typedef struct node{
    int from, to;
    int w;
    bool operator < (node zz){
        return w < zz.w;
    }
}Edge;
typedef struct nn{
    int to;
    int w;
    nn(){}
    nn(LL a, LL b){
        to = a; w = b;
    }
}EEE;

LL ans;
double res;
int t, n, m;
Edge g[maxn * 10];
vector<EEE> e[maxn];
int vis[maxn], pre[maxn];

int findfather(int x){
    return pre[x] = (pre[x] == x ? x : findfather(pre[x]));
}
void join(int x, int y){
    pre[findfather(x)] = findfather(y);
}
void kruskal(){
    int x, y, flag = 0;
    for(int i = 0; i < m; ++i){
        x = findfather(g[i].from);
        y = findfather(g[i].to);

        if(x == y) continue;
        join(x, y);
        ++flag;
        ans += g[i].w;
        e[g[i].from].push_back(nn(g[i].to, g[i].w));
        e[g[i].to].push_back(nn(g[i].from, g[i].w));

        if(flag == n - 1) return;
    }
}
int dfs(int p){
    if(vis[p]) return 0;
    vis[p] = 1;

    int tt = 1, num;
    for(int i = 0; i < e[p].size(); ++i){
        int v = e[p][i].to;
        num = dfs(v);
        tt += num;
        res += (LL)(n - num) * (LL)num * (LL)e[p][i].w;
    }
    return tt;
}
int main(){
    scanf("%d", &t);
    while(t--){
        scanf("%d%d", &n, &m);
        for(int i = 1; i <= n; ++i) {
            pre[i] = i;
            vis[i] = 0;
            e[i].clear();
        }
        for(int i = 0; i < m; ++i){
            scanf("%d%d%d", &g[i].from, &g[i].to, &g[i].w);
        }
        sort(g, g + m);
        ans = 0;
        kruskal();

        res = 0;
        dfs(1);
        printf("%lld %.2lf\n", ans, res / ((n - 1LL) * n / 2.0));
    }
    return 0;
}


### 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() ```
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值