帮我用c++解决这个问题:地铁耗时最短的线路 大湾区某城市地铁线路非常密集,乘客通常需要经过一些出站...

作成日: 2025年4月9日

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質問

帮我用c++解决这个问题:地铁耗时最短的线路
大湾区某城市地铁线路非常密集,乘客通常需要经过一些出站线路来乘坐地铁,为了解决这个问题,地铁公司想要开发一个程序帮助乘客寻找合适的乘坐线路,使得乘客耗时最短。地铁公司可以使用你的算法来准备各条相邻站点之间的数据。
需求表示
时间限制:C/C++ 1000ms,其他语言:2000ms
内存限制:C/C++ 256MB,其他语言:512MB
输入
第一行:N,站点总数 3 <= N <= 26
第二行:乘客的出发和到达站点。
第三行起:相邻站点之间的耗时时间。每行站点一行,站点名称是单个小写字母,每行站点也包含出发和到达站点,输入保证只有一个唯一线路。
结束行:0000
输出
耗时最短的线路
示例1
输入:
12
a e
a b 2
b c 2
c d 2
d e 2
f b 3
b g 3
g h 2
h i 3
j h 2
h e 3
e k 2
k l 4
0000
Use code with caution.
输出:
abcde
Use code with caution.
解释: 输入对应的地铁图如下:
图形解释示例1, 从 a -> b 2分钟, b -> c 2分钟,c->d 2分钟,d->e 2分钟, aw 10分钟, hl 3分钟, gi 2分钟,gh 2分钟,hi 3分钟, jh 2分钟, ho 3分钟,ek 2分钟
线路 a->b->c->d->e 耗时最短
示例2
输入:
12
f k
a b 2
b c 2
c d 2
d e 2
f b 3
b g 3
g h 2
h i 3
j h 2
h e 3
e k 2
k l 4
0000
Use code with caution.
输出:
fbcdek
Use code with caution.
解释: 输入对应的地铁图如下:
图形解释示例2, 从 a -> b 2分钟, b -> c 2分钟,c->d 2分钟,d->e 2分钟, fb 3分钟, bg 3分钟, gh 2分钟,hi 3分钟, jh 2分钟, he 3分钟,ek 2分钟, kl 4分钟
f->b->c->d->e->k 是耗时最短的线路
问题总结:
给定地铁线路图,找到从出发站点到到达站点耗时最短的路径。
关键信息:
站点总数 N (3 <= N <= 26),意味着站点名称可以用小写字母表示。
输入数据以 "0000" 结束。
需要输出最短路径的站点名称序列。
站点名称是单个小写字母

思考

Solving subway route problem

The user asks to solve the problem of finding the fastest subway route using C++. The problem involves determining the route with the smallest total travel time based on a graph representing subway stations and travel times. The input consists of the number of stations, start/destination stops, and several edges with travel times. The problem states that the connections are likely directional, meaning the graph is probably directed. It seems to resemble a shortest path problem, and I can think of algorithms like Dijkstra’s for this.

Clarifying subway problem

The problem specifies that each input line represents an edge between two subway stations with the travel time. For example, "a b 2" means from station 'a' to station 'b' with a 2-minute travel time.

The task is to find the shortest route. I realized the input guarantees one unique shortest route, so no tie-breaking is needed.

To solve it, the code will need to read the stations, start/end points, and the subway connections, then build a graph to calculate the shortest path. The graph will have nodes up to 26 stations.

Deciding graph structure

The station names are letters, and each input line provides a departure station, destination station, and travel time.

It seems the graph should be directed because the paths from stations like "f" to "b" but not "b" to "f" are possible. The problem doesn't explicitly say if it's directed, but the lack of reverse connections in examples suggests that it is.

I'll use Dijkstra's algorithm for this problem, as the graph representation will be simple with adjacency lists or matrices. I'll treat the stations as nodes in the graph and compute the shortest path from the start to the destination station.

Reasoned about shortest subway route for 1m 10s

回答

下面给出一个完整的 C++ 解决方案,利用 Dijkstra 算法求出耗时最短的线路。代码中用邻接表存储图(用 26 个元素的 vector 表示所有字母站点),并且读取第三行开始的每一条边,直到遇到结束标志 "0000"。

下面是代码实现:


cpp
/* * 题目说明:给定一个地铁图,每条边表示两个相邻站点之间的耗时,求出从出发站点到到达站点耗时最短的线路。 * * 解题思路: * 1. 将站点用字母(a ~ z)映射为 0~25 的编号,构建图的邻接表(本题中边为有向边)。 * 2. 使用 Dijkstra 算法求从出发站点到所有其他站点的最短路径。 * 3. 用 parent 数组记录最短路径中的前驱节点,以便回溯还原出完整的线路。 * 4. 最后将站点编号转换为字母输出即可。 * * 输入格式: * 第一行:N,站点总数 (3 <= N <= 26) * 第二行:出发站点和到达站点(用空格分隔,均为单个小写字母) * 第三行起:每行描述一条相邻站点之间的耗时,格式为“起点 终点 耗时” * 结束行:输入"0000"表示结束 * * 输出格式: * 输出耗时最短的站点序列(例如:abcde) */ #include <iostream> #include <vector> #include <string> #include <sstream> #include <queue> #include <limits> using namespace std; int main(){ int N; cin >> N; char start, end; cin >> start >> end; // 由于站点名称为小写字母,最多26个 vector<vector<pair<int, int>>> graph(26); // 读取剩余换行符 string line; getline(cin, line); // 读取各条边的耗时信息,直到遇到"0000" while(getline(cin, line)){ if(line == "0000") break; if(line.empty()) continue; stringstream ss(line); char u, v; int time; ss >> u >> v >> time; int idx_u = u - 'a'; int idx_v = v - 'a'; graph[idx_u].push_back({idx_v, time}); } // Dijkstra 算法 const int INF = numeric_limits<int>::max(); vector<int> dist(26, INF); vector<int> parent(26, -1); int src = start - 'a'; int dst = end - 'a'; dist[src] = 0; // 使用小根堆,存储 pair<距离, 节点编号> priority_queue<pair<int, int>, vector<pair<int, int>>, greater<pair<int, int>>> pq; pq.push({0, src}); while(!pq.empty()){ auto [d, u] = pq.top(); pq.pop(); if(d > dist[u]) continue; if(u == dst) break; // 如果已经到达目标,可以提前结束 for(auto &edge : graph[u]){ int v = edge.first; int w = edge.second; if(dist[u] + w < dist[v]){ dist[v] = dist[u] + w; parent[v] = u; pq.push({dist[v], v}); } } } // 回溯得到最短路径 string result = ""; if(dist[dst] != INF) { vector<char> path; int cur = dst; while(cur != -1){ path.push_back('a' + cur); cur = parent[cur]; } // 反转路径顺序 for(int i = path.size()-1; i >= 0; i--){ result.push_back(path[i]); } } cout << result; return 0; }

代码说明

  1. 图的构建:

    • vector<vector<pair<int,int>>> graph(26); 表示站点图。
    • 每条边读入起点字母、终点字母及其耗时,然后映射为对应的 0~25 的编号后存入邻接表。
  2. 输入读取:

    • 第一行读取站点数 N(虽然实际并不需要使用该值来构建邻接表,只作为题目描述);
    • 第二行读取出发站点和到达站点;
    • 第三行起利用 getline 循环读取每条边,当读到 "0000" 时结束输入读取。
  3. Dijkstra 算法求最短路径:

    • 使用 dist 数组记录每个站点的最短距离,初始值均为无穷大;
    • 使用 parent 数组记录每个站点的前驱,方便后续回溯;
    • 利用优先队列更新每个站点的最短路径。
  4. 路径回溯与输出:

    • 从到达站点开始,通过 parent 数组回溯,获取最短路径的站点顺序,再反转后输出最终的路径字符串。

编译运行时请注意输入格式,确保按要求输入终止符 "0000"。这样就能求得题目要求的“耗时最短的线路”。

質問

帮我用c++解决这个问题:题目描述:
某测试工具升级时总是选择迭代次数最多的补丁版本,已知这些补丁版本的前序版本(即依赖该版本修改发布的新补丁版本),前序版本的个数 <= 1, 且不会存在互为前序版本的情况。请给出最终可以升级的补丁版本,版本号只包含大写字母和数字。
解题要求:
时间限制: C/C++ 2000ms, 其他语言: 4000ms
内存限制: C/C++ 256MB, 其他语言: 512MB
输入:
第一行为记录的版本迭代关系个数 N,范围 [1, 100000]
第二行到 N+1 行: 每行包含两个字符串,第一个字符串为当前版本,第二个字符串为前序版本,用空格隔开。字符串包含字符个数为 [1, 100], 没有前序版本的第二个字符串固定为 NA。
输出:
输出所有迭代次数最多的补丁版本号字符串列表,多个版本号以字典序排列,用空格隔开。
样例1:
输入:
6
CN0010 BF0001
BF0001 AZ0001
AZ0001 NA
BF0010 AZ0001
AW0001 NA
BF0011 AZ0001
Use code with caution.
输出:
CN0010
Use code with caution.
解释:
AZ0001 和 AW0001 没有前序版本,迭代了 0 次;
BF0001, BF0010, BF0011 的前序版本为 AZ0001,迭代了 1 次;
CN0010 的前序版本为 BF0001, BF0001 的前序版本为 AZ0001,迭代了 2 次。
根据要求选择迭代次数最多的补丁版本,因此输出 CN0010。
样例2:
输入:
3
BF0001 AZ0001
AZ0001 NA
BF0011 AZ0001
Use code with caution.
输出:
BF0001 BF0011
Use code with caution.
解释:
AZ0001 没有前序版本,迭代了 0 次;
BF0001 和 BF0011 的前序版本为 AZ0001,迭代了 1 次;

思考

Analyzing upgrade choice

The problem asks us to identify the patch versions with the most iterations from a set of relationships. Each line of input includes a current version and its dependent pre-version, with the relationships forming a tree-like structure (no loops). We are tasked with determining which versions have the most dependencies and output those in lexicographical order. Given the constraints (up to 100,000 relationships and version names up to 100 characters), we’ll need efficient handling of these dependencies to find the solution. Let's focus on how to calculate iteration counts efficiently.

Determining patch chains

Looking at the sample, I see different dependency chains. For instance, "AZ0001" has no pre-version, so it's at iteration 0. Then "BF0001" depends on "AZ0001" (iteration 1), and "CN0010" depends on "BF0001" (iteration 2). Therefore, "CN0010" has the longest chain.

In another example, "BF0001" and "BF0011" both depend on "AZ0001" with iteration 1. Since we need these in lexicographical order, the output is "BF0001 BF0011."

The problem is about calculating these chains and identifying the version(s) with the longest chain length.

Calculating chain lengths

To find chain lengths, I should consider that if a version depends on "NA", its chain length is 0. If it depends on another version, its chain length is one more than that of the parent version. The challenge is efficiently calculating chain lengths since the relationships could form large trees of dependencies. I’ll need to traverse these relationships and use dynamic programming to memoize and avoid deep recursion. I can store dependencies in a dictionary and compute the chain lengths iteratively, considering up to 100,000 relationships.

Identifying final upgrade patches

To solve this, we need to find the versions that are not used as "pre" versions in any other relationship. These are the final patches in the chain. After computing each patch's chain length, we select those with the largest iteration count. We store relations and use a parent tracking system to identify the leaf nodes—those that don't appear as "pre" versions. These will be the candidates for upgrading. Among them, the ones with the longest chains are chosen, and for ties, we return them in lexicographical order.

Implementing patch chain calculation

I need to compute chain lengths for patch versions by following dependencies. Each version's chain is determined by its pre-version: if it's "NA", the chain length is 0; otherwise, the chain length is 1 plus the pre-version's chain length. Using memoization, I'll avoid redundant computations and ensure efficiency. After processing the chains for all current versions, I'll find the leaf nodes—those that do not appear as pre-versions—and calculate their iteration counts. The final candidate versions are those with the highest iteration counts, sorted lexicographically.

Reasoned about patch version iteration for 2m 3s

回答

下面给出一个完整的 C++ 代码实现。思路如下:

  1. 构建依赖关系
    每条输入记录表示“当前版本 依赖版本”。用一个字典(unordered_map)保存每个当前版本对应的依赖版本(即前序版本),同时记录所有当前版本和那些出现在依赖位置(且不为 "NA")的版本。

    • 那些出现在当前版本集合中,但不在“依赖版本”集合中的版本即为最终补丁候选(即没有被其他补丁升级的版本)。
  2. 计算迭代次数
    定义某版本的“迭代次数”为从该版本一路追溯其依赖链直到遇到 “NA”(或没有记录)时的步数。根据题目要求,若依赖为 "NA",迭代次数为 0;否则迭代次数等于其依赖版本的迭代次数加 1。
    为了避免重复计算(或因依赖链过长而导致递归深度太大),我们采用带备忘的迭代法计算每个版本的迭代次数。

  3. 输出结果
    遍历所有最终候选版本,找到迭代次数最大的那个(可能有多个),按字典序排列后输出。

下面是对应的 C++ 代码:


cpp
#include <iostream> #include <string> #include <unordered_map> #include <unordered_set> #include <vector> #include <algorithm> using namespace std; int main(){ ios::sync_with_stdio(false); cin.tie(nullptr); int N; cin >> N; // 保存依赖关系:current_version -> pre_version unordered_map<string, string> pre; // 保存所有出现在当前版本位置的版本号 unordered_set<string> currentSet; // 保存所有出现在依赖(前序版本)位置且不为 "NA" 的版本号 unordered_set<string> nonFinal; for (int i = 0; i < N; i++){ string cur, par; cin >> cur >> par; pre[cur] = par; currentSet.insert(cur); if(par != "NA"){ nonFinal.insert(par); } } // 最终候选:只出现在当前位置,但没有作为依赖出现过 vector<string> finals; for(auto &ver : currentSet){ if(nonFinal.find(ver) == nonFinal.end()){ finals.push_back(ver); } } // memo 记录每个版本的迭代次数 unordered_map<string, int> chainLen; // 采用迭代法求版本 ver 的迭代次数 auto getChainLen = [&](const string &ver) -> int { vector<string> stack; string cur = ver; // 当未找到迭代次数且存在依赖时,向上查找 while (true) { // 若当前版本已经计算过则退出 if(chainLen.find(cur) != chainLen.end()) break; // 如果当前版本没有记录(即没有依赖关系)或者依赖为 "NA",则认为迭代次数为 0 if(pre.find(cur) == pre.end() || pre[cur] == "NA"){ chainLen[cur] = 0; break; } stack.push_back(cur); cur = pre[cur]; } // 此时 cur 对应的迭代次数已知,将栈内依次回填 int base = chainLen[cur]; while(!stack.empty()){ string node = stack.back(); stack.pop_back(); base = base + 1; chainLen[node] = base; } return chainLen[ver]; }; // 遍历所有最终候选,找出迭代次数最大的 int maxChain = -1; vector<string> res; for(auto &patch : finals){ int len = getChainLen(patch); if(len > maxChain){ maxChain = len; res.clear(); res.push_back(patch); } else if(len == maxChain){ res.push_back(patch); } } // 结果按字典序输出(多个版本以空格分隔) sort(res.begin(), res.end()); for (int i = 0; i < res.size(); i++){ cout << res[i] << (i == res.size() - 1 ? "" : " "); } return 0; }

代码说明

  • 构建依赖信息:
    利用 unordered_map<string, string> pre 保存每条记录中当前版本与其前序版本的关系,同时用 currentSet 记录所有出现在“当前版本”的版本号;用 nonFinal 记录所有出现在“前序版本”(且不为 "NA")的版本。这样最终候选版本即为那些只在 currentSet 中出现而不在 nonFinal 中出现的版本。

  • 计算迭代次数:
    使用迭代法(利用栈的方式)计算某版本从其依赖链上升到基底(依赖为 "NA"或无记录)的步数,并用 chainLen 进行备忘以避免重复计算。

  • 输出:
    统计所有最终候选版本中迭代次数最大的版本,并按字典序排列后输出,版本之间用空格分隔。

该程序满足题目要求,在输入样例上运行的效果如下:

样例1输入:

text
6 CN0010 BF0001 BF0001 AZ0001 AZ0001 NA BF0010 AZ0001 AW0001 NA BF0011 AZ0001

程序计算出各个版本的迭代次数(AZ0001:0,BF0001/BF0010/BF0011:1,CN0010:2,AW0001:0),最终候选为 CN0010,输出:

CN0010

样例2输入:

text
3 BF0001 AZ0001 AZ0001 NA BF0011 AZ0001

最终候选为 BF0001 与 BF0011(迭代次数均为1),按字典序输出:

BF0001 BF0011

可以使用 g++ 编译并运行该代码,即可实现题目要求。

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