UVA 1395 Slim Span

本文探讨了一种特殊的生成树——最瘦生成树的问题。通过枚举不同边的组合,找到生成树中最大权值与最小权值之差最小的情况。采用排序与并查集策略,实现了高效求解。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

Given an undirected weighted graph G, you should find one of spanning trees specified as follows. 

The graph G is an ordered pair (VE), where V is a set of vertices {v1v2, ... , vn} and E is a set of undirected edges {e1e2, ... , em}. Each edge e ∈ E has its weight w(e). 

A spanning tree T is a tree (a connected subgraph without cycles) which connects all the n vertices with n - 1 edges. The slimness of a spanning tree T is defined as the difference between the largest weight and the smallest weight among the n - 1 edges of T

Figure 5: A graph G and the weights of the edges 

For example, a graph G in Figure 5(a) has four vertices {v1v2v3v4} and five undirected edges {e1e2e3e4e5}. The weights of the edges are w(e1) = 3, w(e2) = 5, w(e3) = 6, w(e4) = 6, w(e5) = 7 as shown in Figure 5(b). 

Figure 6: Examples of the spanning trees of G

There are several spanning trees for G. Four of them are depicted in Figure 6(a)-(d). The spanning tree Ta in Figure 6(a) has three edges whose weights are 3, 6 and 7. The largest weight is 7 and the smallest weight is 3 so that the slimness of the tree Ta is 4. The slimnesses of spanning trees Tb , Tc and Td shown in Figure 6(b), (c) and (d) are 3, 2 and 1, respectively. You can easily see the slimness of any other spanning tree is greater than or equal to 1, thus the spanning tree Td in Figure 6(d) is one of the slimmest spanning trees whose slimness is 1. 

Your job is to write a program that computes the smallest slimness. 

Input

The input consists of multiple datasets, followed by a line containing two zeros separated by a space. Each dataset has the following format. 

n     m
a1  b1  w1
  .
  .
  .
am  bm  wm

Every input item in a dataset is a non-negative integer. Items in a line are separated by a space. 

n is the number of the vertices and m the number of the edges. You can assume 2 ≤ n ≤ 100 and 0 ≤ m ≤ n(n - 1)/2. ak and bk (k = 1, ... , m) are positive integers less than or equal to n, which represent the two vertices vak and vbk connected by the kth edge ekwk is a positive integer less than or equal to 10000, which indicates the weight of ek . You can assume that the graph G = (VE) is simple, that is, there are no self-loops (that connect the same vertex) nor parallel edges (that are two or more edges whose both ends are the same two vertices). 

Output

For each dataset, if the graph has spanning trees, the smallest slimness among them should be printed. Otherwise, -1 should be printed. An output should not contain extra characters. 

Sample Input

4 5
1 2 3
1 3 5
1 4 6
2 4 6
3 4 7
4 6
1 2 10
1 3 100
1 4 90
2 3 20
2 4 80
3 4 40
2 1
1 2 1
3 0
3 1
1 2 1
3 3
1 2 2
2 3 5
1 3 6
5 10
1 2 110
1 3 120
1 4 130
1 5 120
2 3 110
2 4 120
2 5 130
3 4 120
3 5 110
4 5 120
5 10
1 2 9384
1 3 887
1 4 2778
1 5 6916
2 3 7794
2 4 8336
2 5 5387
3 4 493
3 5 6650
4 5 1422
5 8
1 2 1
2 3 100
3 4 100
4 5 100
1 5 50
2 5 50
3 5 50
4 1 150
0 0

Output for the Sample Input

1
20
0
-1
-1
1
0
1686
50

总结:

一开始认为是另一种标准的生成树,准备重新搞一套选择边的方式,(虽然最后用暴力枚举的方法,但是更优的策略未必不存在),想了半天也没想出怎么搞,但是期间脑海里确实是有闪过,先进性排序,如果直接从小到大的生成树,活着从大到小的生成树,或者从中间开始的生成树可不可以呢,因为这样都是从相邻的中选择的,但是也只是闪过了一下,没有继续思考下去,看过书上的提示以后才发现其中的这种思想的本质就是在枚举答案啊,因为我们每次选择的区间[l,r]那么我们的答案就是w[r]-w[r]啊,好痛心啊,以前只会枚举的时候看见什么都想暴力枚举,现在学的东西越来越多了反倒想不到枚举了!
//
//  main.cpp
//  Slim Span
//
//  Created by 张嘉韬 on 16/8/20.
//  Copyright © 2016年 张嘉韬. All rights reserved.
//

#include <iostream>
#include <cstdio>
#include <cstring>
#include <algorithm>
#include <cmath>
using namespace std;
const int maxn=100+10;
const int inf=1<<30;
int n,m,f[maxn],minimum,maximum;
struct road
{
    int u;
    int v;
    int w;
}roads[maxn*maxn/2];
int cmp(road a,road b)
{
    return a.w<b.w;
}
int getf(int i)
{
    if(f[i]==i) return i;
    else return f[i]=getf(f[i]);
}
void merge(int a,int b,int w)
{
    maximum=max(maximum,w);
    minimum=min(minimum,w);
    int fa=getf(a);
    int fb=getf(b);
    if(fa==fb) return;
    f[fa]=fb;
}
void init()
{
    for(int i=1;i<=n;i++) f[i]=i;
    minimum=inf;
    maximum=-inf;
}
int check()
{
    int cnt=0;
    int father=getf(1);
    for(int i=2;i<=n;i++)
    {
        if(getf(i)!=father) cnt++;
    }
    if(cnt==0) return 1;
    else return 0;
}
int main(int argc, const char * argv[]) {
    //freopen("/Users/zhangjiatao/Documents/暑期训练/input.txt","r",stdin);
    while(scanf("%d%d",&n,&m))
    {
        if(n==0&&m==0) break;
        for(int i=1;i<=m;i++) scanf("%d%d%d",&roads[i].u,&roads[i].v,&roads[i].w);
        sort(roads+1,roads+m+1,cmp);
        int silm=inf;
        for(int l=1;l<=m;l++)
        {
            init();
            for(int r=l;r<=m;r++)
            {
                if(getf(roads[r].u)!=getf(roads[r].v))
                {
                    merge(roads[r].u,roads[r].v,roads[r].w);
                    if(check()==1)
                    {
                        if(maximum-minimum<silm) silm=maximum-minimum;
                        break;
                    }
                }
            }
        }
        if(silm==inf) printf("-1\n");
        else printf("%d\n",silm);
    }
    return 0;
}


内容概要:本文档详细介绍了Analog Devices公司生产的AD8436真均方根-直流(RMS-to-DC)转换器的技术细节及其应用场景。AD8436由三个独立模块构成:轨到轨FET输入放大器、高动态范围均方根计算内核和精密轨到轨输出放大器。该器件不仅体积小巧、功耗低,而且具有广泛的输入电压范围和快速响应特性。文档涵盖了AD8436的工作原理、配置选项、外部组件选择(如电容)、增益调节、单电源供电、电流互感器配置、接地故障检测、三相电源监测等方面的内容。此外,还特别强调了PCB设计注意事项和误差源分析,旨在帮助工程师更好地理解和应用这款高性能的RMS-DC转换器。 适合人群:从事模拟电路设计的专业工程师和技术人员,尤其是那些需要精确测量交流电信号均方根值的应用开发者。 使用场景及目标:①用于工业自动化、医疗设备、电力监控等领域,实现对交流电压或电流的精准测量;②适用于手持式数字万用表及其他便携式仪器仪表,提供高效的单电源解决方案;③在电流互感器配置中,用于检测微小的电流变化,保障电气安全;④应用于三相电力系统监控,优化建立时间和转换精度。 其他说明:为了确保最佳性能,文档推荐使用高质量的电容器件,并给出了详细的PCB布局指导。同时提醒用户关注电介质吸收和泄漏电流等因素对测量准确性的影响。
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