PAT (Advanced Level) Practice 1087

本文探讨了在多个城市间找到成本最低且幸福感最大的路线问题,通过Dijkstra算法结合深度优先搜索(DFS),实现了从任意城市到罗马的最优路径规划。代码示例详细展示了如何处理输入数据,构建城市间的连接,并求解最优解。

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1087 All Roads Lead to Rome (30 分)

Indeed there are many different tourist routes from our city to Rome. You are supposed to find your clients the route with the least cost while gaining the most happiness.

Input Specification:

Each input file contains one test case. For each case, the first line contains 2 positive integers N (2≤N≤200), the number of cities, and K, the total number of routes between pairs of cities; followed by the name of the starting city. The next N−1 lines each gives the name of a city and an integer that represents the happiness one can gain from that city, except the starting city. Then K lines follow, each describes a route between two cities in the format City1 City2 Cost. Here the name of a city is a string of 3 capital English letters, and the destination is always ROM which represents Rome.

Output Specification:

For each test case, we are supposed to find the route with the least cost. If such a route is not unique, the one with the maximum happiness will be recommanded. If such a route is still not unique, then we output the one with the maximum average happiness -- it is guaranteed by the judge that such a solution exists and is unique.

Hence in the first line of output, you must print 4 numbers: the number of different routes with the least cost, the cost, the happiness, and the average happiness (take the integer part only) of the recommanded route. Then in the next line, you are supposed to print the route in the format City1->City2->...->ROM.

Sample Input:

6 7 HZH
ROM 100
PKN 40
GDN 55
PRS 95
BLN 80
ROM GDN 1
BLN ROM 1
HZH PKN 1
PRS ROM 2
BLN HZH 2
PKN GDN 1
HZH PRS 1

Sample Output:

3 3 195 97
HZH->PRS->ROM

分析:Dijkstra + DFS。用DFS得到所有最短路径前驱,储存在vector<int>的pre数组中。之后用DFS遍历所有前驱节点,寻找符合题意的路径。

代码:

#include<iostream>
#include<algorithm>
#include<vector>
#include<map>
#include<string>
#define MAXN 402
#define INF 0x3fffffff
using namespace std;
int G[MAXN][MAXN] = { 0 };
int d[MAXN];
int visit[MAXN] = { 0 };
int C[MAXN] = { 0 };
vector<int> pre[MAXN];
map<int, string> intToString;
map<string, int> stringToInt;
int N, K;
string starting;
int numCity = 0;
int S, D;
int num[MAXN];
vector<int> path, tempPath;
int mostHappiness = -1;
void dfs(int v) {
	tempPath.push_back(v);
	if (v == S) {
		int happiness = 0;
		for (int i = 0; i < tempPath.size(); i++) {
			happiness += C[tempPath[i]];
		}
		if (happiness > mostHappiness) {
			mostHappiness = happiness;
			path = tempPath;
		} else if (happiness == mostHappiness) {
			if (happiness / (tempPath.size() - 1) > mostHappiness / (path.size() - 1)) {
				path = tempPath;
			}
		}
	}
	for (int i = 0; i < pre[v].size(); i++) {
		dfs(pre[v][i]);
	}
	tempPath.pop_back();

}
void dijkstra() {
	for (int i = 0; i < N; i++) {
		num[i] = 1;
	}
	d[S] = 0;
	for (int i = 0; i < N; i++) {
		int u = -1, minN = INF;
		for (int j = 0; j < N; j++) {
			if (d[j] < minN && visit[j] == 0) {
				u = j;
				minN = d[j];
			}
		}
		if (u == -1) {
			return;
		}
		visit[u] = 1;
		for (int v = 0; v < N; v++) {
			if (G[u][v] != INF && visit[v] == 0) {
				if (d[v] > d[u] + G[u][v]) {
					d[v] = d[u] + G[u][v];
					num[v] = num[u];
					pre[v].clear();
					pre[v].push_back(u);
				} else if (d[v] == d[u] + G[u][v]) {
					num[v] += num[u];
					pre[v].push_back(u);
				}
			}
		}
	}
}
int getID(string name) {
	if (stringToInt.count(name) == 0) {
		stringToInt[name] = numCity;
		intToString[numCity] = name;
		return numCity++;
	} else {
		return stringToInt[name];
	}
}
int main() {
	fill(G[0], G[0] + MAXN * MAXN, INF);
	fill(d, d + MAXN, INF);
	cin >> N >> K >> starting;
	S = getID(starting);
	D = getID("ROM");
	getchar();
	for (int i = 0; i < N - 1; i++) {
		string City;
		int temp;
		cin >> City >> temp;
		int id = getID(City);
		C[id] = temp;
	}
	for (int i = 0; i < K; i++) {
		string City1, City2;
		int temp;
		cin >> City1 >> City2 >> temp;
		int id1 = getID(City1);
		int id2 = getID(City2);
		G[id1][id2] = G[id2][id1] = temp;
	}
	dijkstra();
	dfs(D);
	cout << num[D] << ' ' << d[D] << ' ' << mostHappiness << ' ' << mostHappiness / (path.size() - 1) << endl;
	for (int i = path.size() - 1; i >= 0; i--) {
		if (i != 0) {
			cout << intToString[path[i]] << "->";
		} else {
			cout << intToString[path[i]] << endl;
		}
	}
	return 0;
}

 

### PAT 基本级别练习的相关资料 PAT(Programming Ability Test)是一项针对编程能力的标准化考试,其基本级别主要考察考生的基础编程技能和逻辑思维能力。以下是关于 PAT 基本级别的练习题目及相关解决方案的内容。 #### 题目分类 PAT 基本级别的题目通常分为以下几个类别: 1. **字符串处理**:涉及字符串的操作,如反转、查找子串等。 2. **数组操作**:包括数组排序、去重、统计等问题。 3. **简单算法实现**:如计算阶乘、判断素数等基础算法。 4. **输入输出格式化**:要求按照特定格式读取数据并输出结果。 以下是一些典型的 PAT 基本级别练习题及其解决思路: --- #### 示例题目 1: 字符串反转 **描述**: 输入一个字符串,将其逆序输出。 **解法**: 可以通过 Python 中的切片功能轻松实现字符串反转。 ```python def reverse_string(s): return s[::-1] # 测试用例 input_str = input() print(reverse_string(input_str)) ``` 此代码利用了 Python 切片语法 `s[start:end:step]`,其中步长为 `-1` 表示反向遍历字符串[^4]。 --- #### 示例题目 2: 数组求和 **描述**: 给定一组整数,求数组中所有元素的总和。 **解法**: 通过循环累加或者内置函数 `sum()` 实现数组求和。 ```python def array_sum(arr): return sum(arr) # 测试用例 numbers = list(map(int, input().split())) print(array_sum(numbers)) ``` 上述代码中,`map()` 函数用于将输入转换为整型列表,而 `sum()` 是 Python 的内置函数,能够高效完成求和任务[^5]。 --- #### 示例题目 3: 计算阶乘 **描述**: 输入一个正整数 \( n \),输出它的阶乘 \( n! \)。 **解法**: 使用递归或迭代方式均可实现阶乘计算。 ```python def factorial(n): if n == 0 or n == 1: return 1 result = 1 for i in range(2, n + 1): result *= i return result # 测试用例 n = int(input()) print(factorial(n)) ``` 该程序采用了迭代方法避免栈溢出的风险,在实际应用中更为稳健[^6]。 --- #### 示例题目 4: 判断素数 **描述**: 输入一个正整数 \( m \),判断它是否为素数。 **解法**: 素数是指仅能被 1 和自身整除的大于 1 的自然数。可通过试除法验证。 ```python import math def is_prime(m): if m <= 1: return False sqrt_m = int(math.sqrt(m)) + 1 for i in range(2, sqrt_m): if m % i == 0: return False return True # 测试用例 m = int(input()) if is_prime(m): print("Yes") else: print("No") ``` 在此代码片段中,引入了平方根优化技术以减少不必要的运算次数[^7]。 --- ### 总结 以上展示了几个常见的 PAT 基础级问题以及对应的解决方案。这些例子涵盖了字符串操作、数组处理、数学计算等多个方面,有助于初学者熟悉 PAT 考试的形式与难度。
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