Problem A

本文介绍了一个经典的图论问题——寻找使所有节点相连的最小生成树,并通过Prim算法实现这一目标。文章提供了完整的代码示例,解释了如何通过迭代选择最短边来构建最小生成树。
Problem Description
There are N villages, which are numbered from 1 to N, and you should build some roads such that every two villages can connect to each other. We say two village A and B are connected, if and only if there is a road between A and B, or there exists a village C such that there is a road between A and C, and C and B are connected. <br><br>We know that there are already some roads between some villages and your job is the build some roads such that all the villages are connect and the length of all the roads built is minimum.<br>
 

Input
The first line is an integer N (3 <= N <= 100), which is the number of villages. Then come N lines, the i-th of which contains N integers, and the j-th of these N integers is the distance (the distance should be an integer within [1, 1000]) between village i and village j.<br><br>Then there is an integer Q (0 <= Q <= N * (N + 1) / 2). Then come Q lines, each line contains two integers a and b (1 <= a < b <= N), which means the road between village a and village b has been built.<br>
 

Output
You should output a line contains an integer, which is the length of all the roads to be built such that all the villages are connected, and this value is minimum. <br>
 

Sample Input
3 0 990 692 990 0 179 692 179 0 1 1 2
 

Sample Output
179
简单题意:
  现在有N个村子,编号为1-N,需要建立公路使得每两个村子可以相互连通。现在给出一个各个村子之间的距离地图,以及已经连接的村子的编号。现在需要编写一个程序,求出使得任意两个村子可以连通的所修建的最短的公路距离。
解题思路形成过程;
  和老师课堂上讲的算法有异曲同工之处,课堂上的是求出最小连通图,而本题是求出最小生成树。但是,为了求出最短距离,就少了一部分代码。所以,用上数据结构中的Prim算法,求出最小生成树,然后解决问题。
感想:
  图这一个专题感觉会比以往难写算法。只有见得多了,才可以运用已知求出未知。
AC代码:
#include<iostream>
#include<cstdio>
#include<cstring>
using namespace std;
const int N=110;
const int INF=0x3f3f3f3f;
int n,ans;
int map[N][N],dis[N],vis[N];
void Prim()
{
    int i;
    for(i=1;i<=n;i++)
    {
        dis[i]=map[1][i];
        vis[i]=0;
    }
    dis[1]=0;
    vis[1]=1;
    int j,k,tmp;
    for(i=1;i<=n;i++){
        tmp=INF;
        for(j=1;j<=n;j++)
            if(!vis[j] && tmp>dis[j]){
                k=j;
                tmp=dis[j];
            }
        if(tmp==INF)
            break;
        vis[k]=1;
        ans+=dis[k];
        for(j=1;j<=n;j++)
            if(!vis[j] && dis[j]>map[k][j])
                dis[j]=map[k][j];
    }
}
int main()
{
    while(~scanf("%d",&n))
        {
        for(int i=1;i<=n;i++)
            for(int j=1;j<=n;j++)
                scanf("%d",&map[i][j]);
        int q,a,b;
        scanf("%d",&q);
        while(q--)
        {
            scanf("%d%d",&a,&b);
            map[a][b]=map[b][a]=0;
        }
        ans=0;
        Prim();
        printf("%d\n",ans);
    }
    return 0;
}
【论文复现】一种基于价格弹性矩阵的居民峰谷分时电价激励策略【需求响应】(Matlab代码实现)内容概要:本文介绍了一种基于价格弹性矩阵的居民峰谷分时电价激励策略,旨在通过需求响应机制优化电力系统的负荷分布。该研究利用Matlab进行代码实现,构建了居民用电行为与电价变动之间的价格弹性模型,通过分析不同时间段电价调整对用户用电习惯的影响,设计合理的峰谷电价方案,引导用户错峰用电,从而实现电网负荷的削峰填谷,提升电力系统运行效率与稳定性。文中详细阐述了价格弹性矩阵的构建方法、优化目标函数的设计以及求解算法的实现过程,并通过仿真验证了所提策略的有效性。; 适合人群:具备一定电力系统基础知识和Matlab编程能力,从事需求响应、电价机制研究或智能电网优化等相关领域的科研人员及研究生。; 使用场景及目标:①研究居民用电行为对电价变化的响应特性;②设计并仿真基于价格弹性矩阵的峰谷分时电价激励策略;③实现需求响应下的电力负荷优化调度;④为电力公司制定科学合理的电价政策提供理论支持和技术工具。; 阅读建议:建议读者结合提供的Matlab代码进行实践操作,深入理解价格弹性建模与优化求解过程,同时可参考文中方法拓展至其他需求响应场景,如工业用户、商业楼宇等,进一步提升研究的广度与深度。
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