2016江苏省CPC省赛 I - Itinerary Planning

本文介绍了一种利用SPFA算法解决公交路线费用最小化问题的方法。在一个包含不同类型的公交线路(付费和免费)的城市中,通过邻接表实现SPFA算法来找到从起点到终点最经济的路线。

Description

Mike moved to a new city.

There are bus stations in the city, each has a unique name. Each bus has its designated schedule, and sequentially docks at a series of bus stations. Bus lines are bi-directional, and thus you can get on the bus at a station, and get off at any other station in that bus' line. The city provides two kinds of bus services:

1. Type A: each ride costs $2.

2. Type B: rides are completely free of charge.

Given all bus lines in the city, a source station and a destination station, you should help Mike to find the cheapest ride plan to reach the destination from the source.

Input

First line: a positive integer T (T <= 10) indicating the number of test cases.

There are T cases following. In each case, the rst line contains n (1 <= n <= 1,000) indicating the number of bus lines. Then followed by n lines, each of which describes a bus line in the format of t k s1 s2 ... sk (1 <= k <= 10). Speci cally, t is the type of the bus (either A or B), k denotes the number of bus stations in that line, while strings s1,s2,... sk list names of these stations (a bus line may contain duplicated stations) The last line of the case contains two strings: Mike's source s and destination t. All bus station names are case-sensitive alphabets and is no longer than 20. Input guarantees the destination to be reachable.

Output

For each test case: output "Case #x: ans" (without quotes), where x is the number of the case, and ans is the minimum amount of money to reach the destination. 

Sample Input

1
3
A 5 NJU ZSL XJK YT ATZX
B 3 XJK HSDWY MGQ
A 3 HSDWY NJZ MGQ
NJU NJZ

Sample Output

Case #1: 4

spfa的应用,邻接矩阵开不出来,使用邻接表。

#include<cstdio>
#include<iostream>
#include<vector>
#include<queue>
#include<cstring>
#include<map>
using namespace std;
#define MAX 10005
#define INF 0x3f3f3f3f
struct Edge{
	int from,to,weight;
	Edge(int u,int v,int w):from(u),to(v),weight(w){};
};
vector<Edge> E;
vector<int> G[MAX];
void add_edge(int u,int v,int w)
{
	E.push_back(Edge(u,v,w));
	G[u].push_back(E.size()-1);
}
map<string,int> No;
void init()
{
	E.clear();
	No.clear();
	for (int i = 0; i<MAX; i++) G[i].clear();
}
bool vis[MAX];
int d[MAX];
void spfa(int st)
{
	memset(d,INF,sizeof(d));
	memset(vis,false,sizeof(vis));
	queue<int> q;
	q.push(st);
	d[st]=0;
	vis[st]=1;
	while (!q.empty())
	{
		int u=q.front(); 
		q.pop(); 
		vis[u]=0;
		for(int i=0;i<G[u].size();i++)
		{
			Edge &e=E[G[u][i]];
			int tmp=d[e.to];
			if(d[e.to]>d[e.from]+e.weight) d[e.to]=d[e.from]+e.weight;
			if(d[e.to]<tmp && !vis[e.to])
			{
				q.push(e.to);
				vis[e.to]=1;
			}
		}
	}
}

int main()
{
	int n,t;
	scanf("%d",&t);
	for(int kase=1;kase<=t;kase++)
	{
		init();
		scanf("%d",&n);
		int cnt=1;
		for(int i=1;i<=n;i++)
		{
			char type;
			int stop_num;
			string stop[12];
			cin>>type>>stop_num;
			for(int j=1;j<=stop_num;j++)
			{
				cin>>stop[j];
				if(No.count(stop[j])==0) No[stop[j]] = cnt++;
			}
			for(int u=1;u<=stop_num;u++)
			{
				for(int v=u+1;v<=stop_num;v++)
				{
					int weight=(type == 'A')?2:0;
					add_edge(No[stop[u]], No[stop[v]], weight);
					add_edge(No[stop[v]], No[stop[u]], weight);
				}
			}
		}
		string st,ed;
		cin>>st>>ed;
		spfa(No[st]);
		printf("Case #%d: %d\n",kase,d[No[ed]]);
	}
}


【直流微电网】径向直流微电网的状态空间建模与线性化:一种耦合DC-DC变换器状态空间平均模型的方法 (Matlab代码实现)内容概要:本文介绍了径向直流微电网的状态空间建模与线性化方法,重点提出了一种基于耦合DC-DC变换器状态空间平均模型的建模策略。该方法通过对系统中多个相互耦合的DC-DC变换器进行统一建模,构建出整个微电网的集中状态空间模型,并在此基础上实施线性化处理,便于后续的小信号分析与稳定性研究。文中详细阐述了建模过程中的关键步骤,包括电路拓扑分析、状态变量选取、平均化处理以及雅可比矩阵的推导,最终通过Matlab代码实现模型仿真验证,展示了该方法在动态响应分析和控制器设计中的有效性。; 适合人群:具备电力电子、自动控制理论基础,熟悉Matlab/Simulink仿真工具,从事微电网、新能源系统建模与控制研究的研究生、科研人员及工程技术人员。; 使用场景及目标:①掌握直流微电网中多变换器系统的统一建模方法;②理解状态空间平均法在非线性电力电子系统中的应用;③实现系统线性化并用于稳定性分析与控制器设计;④通过Matlab代码复现和扩展模型,服务于科研仿真与教学实践。; 阅读建议:建议读者结合Matlab代码逐步理解建模流程,重点关注状态变量的选择与平均化处理的数学推导,同时可尝试修改系统参数或拓扑结构以加深对模型通用性和适应性的理解。
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