Bus System HDU - 1690 Foyd

公交费用计算与最短路径算法
本文介绍了一个基于距离的公交费用计算问题,通过构建图模型并运用Floyd算法解决从任意站点到其他站点的最低费用计算。文章详细解释了如何根据站点坐标和费用表构建图,并使用64位整型确保精度。

一、内容

 Because of the huge population of China, public transportation is very important. Bus is an important transportation method in traditional public transportation system. And it’s still playing an important role even now.
The bus system of City X is quite strange. Unlike other city’s system, the cost of ticket is calculated based on the distance between the two stations. Here is a list which describes the relationship between the distance and the cost.
Your neighbor is a person who is a really miser. He asked you to help him to calculate the minimum cost between the two stations he listed. Can you solve this problem for him?
To simplify this problem, you can assume that all the stations are located on a straight line. We use x-coordinates to describe the stations’ positions.

Input

The input consists of several test cases. There is a single number above all, the number of cases. There are no more than 20 cases.
Each case contains eight integers on the first line, which are L1, L2, L3, L4, C1, C2, C3, C4, each number is non-negative and not larger than 1,000,000,000. You can also assume that L1<=L2<=L3<=L4.
Two integers, n and m, are given next, representing the number of the stations and questions. Each of the next n lines contains one integer, representing the x-coordinate of the ith station. Each of the next m lines contains two integers, representing the start point and the destination.
In all of the questions, the start point will be different from the destination.
For each case,2<=N<=100,0<=M<=500, each x-coordinate is between -1,000,000,000 and 1,000,000,000, and no two x-coordinates will have the same value.

Output

For each question, if the two stations are attainable, print the minimum cost between them. Otherwise, print “Station X and station Y are not attainable.” Use the format in the sample.

Sample Input

2
1 2 3 4 1 3 5 7
4 2
1
2
3
4
1 4
4 1
1 2 3 4 1 3 5 7
4 1
1
2
3
10
1 4

Sample Output

Case 1:
The minimum cost between station 1 and station 4 is 3.
The minimum cost between station 4 and station 1 is 3.
Case 2:
Station 1 and station 4 are not attainable.

二、思路

  • 题目给了一个表代表每个路径长度的花费。 然后给出了一些点的坐标,那么我们可以根据这些点的坐标和这个表进行建图,将每个点都相互建立一条边,权值就是路程的花费 。 最后求一次floyd输出答案即可。
  • 由于题目所给的花费较大, 那么必须使用64位整型。

三、代码

#include <cstdio>
#include <cmath>
#include <cstring> 
#include <algorithm>
using namespace std;
typedef long long ll;
const int N = 105;
const ll INF = 1e15;
ll g[N][N];
int  n, m, t, x[5], c[5], d[N], u, v; 
void floyd() {
	for (int k = 1; k <= n; k++) {
		for (int i = 1; i <= n; i++) {
			for (int j = 1; j <= n; j++) {
				g[i][j] = min(g[i][j], g[i][k] + g[k][j]);
			}
		}
	}
}
int abs(int a) {
	return a > 0 ? a : -a; 
}
int main() {
	scanf("%d", &t);
	for (int ci = 1; ci <= t; ci++) {
		for (int i = 1; i <= 4; i++) scanf("%d", x + i);
		for (int i = 1; i <= 4; i++) scanf("%d", c + i);
		scanf("%d%d", &n, &m);
		for (int i = 1; i <= n; i++) scanf("%d", d + i);
		//建图  每2个点都建立一条边
		memset(g, 0x3f, sizeof(g));
		for (int i = 1; i <= n; i++) g[i][i] = 0; 
		for (int i = 1; i <= n; i++) {
			for (int j = i + 1; j <= n; j++) {
				int dis = abs(d[i] - d[j]); //可能是相减负数
				ll w = INF;
				for (int k = 1; k <= 4; k++) {
					if (dis <= x[k]) {
						w = c[k]; //求出这段路径的花费
						break;
					}
				}
				g[i][j] = g[j][i] = min(g[i][j], w);
			}
		}	
		floyd();
		printf("Case %d:\n", ci);
		for (int i = 1; i <= m; i++) {
			scanf("%d%d", &u, &v);
			if (g[u][v] == INF) {
				printf("Station %d and station %d are not attainable.\n", u, v);
			} else {
				printf("The minimum cost between station %d and station %d is %lld.\n", u, v, g[u][v]);
			}
		}
	}
	return 0;
} 
### 关于HDU - 6609 的题目解析 由于当前未提供具体关于 HDU - 6609 题目的详细描述,以下是基于一般算法竞赛题型可能涉及的内容进行推测和解答。 #### 可能的题目背景 假设该题目属于动态规划类问题(类似于多重背包问题),其核心在于优化资源分配或路径选择。此类问题通常会给出一组物品及其属性(如重量、价值等)以及约束条件(如容量限制)。目标是最优地选取某些物品使得满足特定的目标函数[^2]。 #### 动态转移方程设计 如果此题确实是一个变种的背包问题,则可以采用如下状态定义方法: 设 `dp[i][j]` 表示前 i 种物品,在某种条件下达到 j 值时的最大收益或者最小代价。对于每一种新加入考虑范围内的物体 k ,更新规则可能是这样的形式: ```python for i in range(n): for s in range(V, w[k]-1, -1): dp[s] = max(dp[s], dp[s-w[k]] + v[k]) ``` 这里需要注意边界情况处理以及初始化设置合理值来保证计算准确性。 另外还有一种可能性就是它涉及到组合数学方面知识或者是图论最短路等相关知识点。如果是后者的话那么就需要构建相应的邻接表表示图形结构并通过Dijkstra/Bellman-Ford/Floyd-Warshall等经典算法求解两点间距离等问题了[^4]。 最后按照输出格式要求打印结果字符串"Case #X: Y"[^3]。 #### 示例代码片段 下面展示了一个简单的伪代码框架用于解决上述提到类型的DP问题: ```python def solve(): t=int(input()) res=[] cas=1 while(t>0): n,k=list(map(int,input().split())) # Initialize your data structures here ans=find_min_unhappiness() # Implement function find_min_unhappiness() res.append(f'Case #{cas}: {round(ans)}') cas+=1 t-=1 print("\n".join(res)) solve() ```
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