POJ-1797Heavy Transportation(最短路)

本文介绍了一个基于Dijkstra算法修改版的问题解决方法,旨在找出城市规划中从起点到终点的最大运输重量,适用于不超过1000个节点的场景。

Heavy Transportation

Time Limit: 3000MSMemory Limit: 30000K
Total Submissions: 76679Accepted: 18675

Description

Background
Hugo Heavy is happy. After the breakdown of the Cargolifter project he can now expand business. But he needs a clever man who tells him whether there really is a way from the place his customer has build his giant steel crane to the place where it is needed on which all streets can carry the weight.
Fortunately he already has a plan of the city with all streets and bridges and all the allowed weights.Unfortunately he has no idea how to find the the maximum weight capacity in order to tell his customer how heavy the crane may become. But you surely know.

Problem
You are given the plan of the city, described by the streets (with weight limits) between the crossings, which are numbered from 1 to n. Your task is to find the maximum weight that can be transported from crossing 1 (Hugo's place) to crossing n (the customer's place). You may assume that there is at least one path. All streets can be travelled in both directions.

Input

The first line contains the number of scenarios (city plans). For each city the number n of street crossings (1 <= n <= 1000) and number m of streets are given on the first line. The following m lines contain triples of integers specifying start and end crossing of the street and the maximum allowed weight, which is positive and not larger than 1000000. There will be at most one street between each pair of crossings.

Output

The output for every scenario begins with a line containing "Scenario #i:", where i is the number of the scenario starting at 1. Then print a single line containing the maximum allowed weight that Hugo can transport to the customer. Terminate the output for the scenario with a blank line.

Sample Input

1
3 3
1 2 3
1 3 4
2 3 5

Sample Output

Scenario #1:
4

Source

TUD Programming Contest 2004, Darmstadt, Germany

数据大小在1000,用dijkstra算法。

你的任务是找到从路口 1到路口 n(客户的地方)可以运输的最大重量”

步骤:

1.把dijkstra算法找最短的一条边,改成找最长的。

2.扩展的条件也相应的做出改变

//C
#include<stdio.h>
#include<string.h>
using namespace std;
const int inf=-0x3f3f3f3f;
int n,m,a[1010][1010],book[1010],dis[1010];

void dijkstra()
{
	int u;
	memset(book,0,sizeof(book));
	for(int i=1;i<=n;i++)
	dis[i]=a[1][i];
	book[1]=1;dis[1]=0;
	for(int i=1;i<n;i++)
	{
		int maxx=inf;
		for(int j=1;j<=n;j++)
		{
			if(book[j]==0&&dis[j]>maxx)
			{
				maxx=dis[j];
				u=j;
			}
		}
		book[u]=1;
		for(int v=1;v<=n;v++)
		{
			if(a[u][v]>inf&&dis[u]>dis[v]&&a[u][v]>dis[v])//1. 5.
			{
				if(dis[u]>a[u][v])
				dis[v]=a[u][v];
				else
				dis[v]=dis[u];
			}
		}
	}
}
int main()
{
	int T;scanf("%d",&T);
	int countt=1;
	while(T--)
	{
		
		int x1,x2,s;
		scanf("%d%d",&n,&m);
		memset(a,inf,sizeof(a));//4.
		for(int i=1;i<=m;i++)
		{
			scanf("%d%d%d",&x1,&x2,&s);
			if(s>a[x1][x2])//2.
			a[x1][x2]=a[x2][x1]=s;
		}
		dijkstra();
		printf("Scenario #%d:\n",countt++);
		printf("%d\n",dis[n]);//3.
		printf("\n");
	}
	return 0;
}

内容概要:本文档介绍了基于3D FDTD(时域有限差分)方法在MATLAB平台上对微带线馈电的矩形天线进行仿真分析的技术方案,重点在于模拟超MATLAB基于3D FDTD的微带线馈矩形天线分析[用于模拟超宽带脉冲通过线馈矩形天线的传播,以计算微带结构的回波损耗参数]宽带脉冲信号通过天线结构的传播过程,并计算微带结构的回波损耗参数(S11),以评估天线的匹配性能和辐射特性。该方法通过建立三维电磁场模型,精确求解麦克斯韦方程组,适用于高频电磁仿真,能够有效分析天线在宽频带内的响应特性。文档还提及该资源属于一个涵盖多个科研方向的综合性MATLAB仿真资源包,涉及通信、信号处理、电力系统、机器学习等多个领域。; 适合人群:具备电磁场与微波技术基础知识,熟悉MATLAB编程及数值仿真的高校研究生、科研人员及通信工程领域技术人员。; 使用场景及目标:① 掌握3D FDTD方法在天线仿真中的具体实现流程;② 分析微带天线的回波损耗特性,优化天线设计参数以提升宽带匹配性能;③ 学习复杂电磁问题的数值建模与仿真技巧,拓展在射频与无线通信领域的研究能力。; 阅读建议:建议读者结合电磁理论基础,仔细理解FDTD算法的离散化过程和边界条件设置,运行并调试提供的MATLAB代码,通过调整天线几何尺寸和材料参数观察回波损耗曲线的变化,从而深入掌握仿真原理与工程应用方法。
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