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]]);
	}
}


内容概要:本文详细介绍了“秒杀商城”微服务架构的设计与实战全过程,涵盖系统从需求分析、服务拆分、技术选型到核心功能开发、分布式事务处理、容器化部署及监控链路追踪的完整流程。重点解决了高并发场景下的超卖问题,采用Redis预减库存、消息队列削峰、数据库乐观锁等手段保障数据一致性,并通过Nacos实现服务注册发现与配置管理,利用Seata处理跨服务分布式事务,结合RabbitMQ实现异步下单,提升系统吞吐能力。同时,项目支持Docker Compose快速部署和Kubernetes生产级编排,集成Sleuth+Zipkin链路追踪与Prometheus+Grafana监控体系,构建可观测性强的微服务系统。; 适合人群:具备Java基础和Spring Boot开发经验,熟悉微服务基本概念的中高级研发人员,尤其是希望深入理解高并发系统设计、分布式事务、服务治理等核心技术的开发者;适合工作2-5年、有志于转型微服务或提升架构能力的工程师; 使用场景及目标:①学习如何基于Spring Cloud Alibaba构建完整的微服务项目;②掌握秒杀场景下高并发、超卖控制、异步化、削峰填谷等关键技术方案;③实践分布式事务(Seata)、服务熔断降级、链路追踪、统一配置中心等企业级中间件的应用;④完成从本地开发到容器化部署的全流程落地; 阅读建议:建议按照文档提供的七个阶段循序渐进地动手实践,重点关注秒杀流程设计、服务间通信机制、分布式事务实现和系统性能优化部分,结合代码调试与监控工具深入理解各组件协作原理,真正掌握高并发微服务系统的构建能力。
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