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332. 重新安排行程

题目描述

给你一份航线列表 tickets ,其中 tickets[i] = [fromi, toi] 表示飞机出发和降落的机场地点。请你对该行程进行重新规划排序。

所有这些机票都属于一个从 JFK(肯尼迪国际机场)出发的先生,所以该行程必须从 JFK 开始。如果存在多种有效的行程,请你按字典排序返回最小的行程组合。

  • 例如,行程 ["JFK", "LGA"]["JFK", "LGB"] 相比就更小,排序更靠前。

假定所有机票至少存在一种合理的行程。且所有的机票 必须都用一次 且 只能用一次。

 

示例 1:

输入:tickets = [["MUC","LHR"],["JFK","MUC"],["SFO","SJC"],["LHR","SFO"]]
输出:["JFK","MUC","LHR","SFO","SJC"]

示例 2:

输入:tickets = [["JFK","SFO"],["JFK","ATL"],["SFO","ATL"],["ATL","JFK"],["ATL","SFO"]]
输出:["JFK","ATL","JFK","SFO","ATL","SFO"]
解释:另一种有效的行程是 ["JFK","SFO","ATL","JFK","ATL","SFO"] ,但是它字典排序更大更靠后。

 

提示:

  • 1 <= tickets.length <= 300
  • tickets[i].length == 2
  • fromi.length == 3
  • toi.length == 3
  • fromitoi 由大写英文字母组成
  • fromi != toi

解法

方法一:欧拉路径

题目实际上是给定 $n$ 个点和 $m$ 条边,要求从指定的起点出发,经过所有的边恰好一次,使得路径字典序最小。这是一个典型的欧拉路径问题。

由于本题保证了至少存在一种合理的行程,因此,我们直接利用 Hierholzer 算法,输出从起点出发的欧拉路径即可。

时间复杂度 $O(m \times \log m)$,空间复杂度 $O(m)$。其中 $m$ 是边的数量。

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class Solution:
    def findItinerary(self, tickets: List[List[str]]) -> List[str]:
        def dfs(f: str):
            while g[f]:
                dfs(g[f].pop())
            ans.append(f)

        g = defaultdict(list)
        for f, t in sorted(tickets, reverse=True):
            g[f].append(t)
        ans = []
        dfs("JFK")
        return ans[::-1]
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class Solution {
    private Map<String, List<String>> g = new HashMap<>();
    private List<String> ans = new ArrayList<>();

    public List<String> findItinerary(List<List<String>> tickets) {
        Collections.sort(tickets, (a, b) -> b.get(1).compareTo(a.get(1)));
        for (List<String> ticket : tickets) {
            g.computeIfAbsent(ticket.get(0), k -> new ArrayList<>()).add(ticket.get(1));
        }
        dfs("JFK");
        Collections.reverse(ans);
        return ans;
    }

    private void dfs(String f) {
        while (g.containsKey(f) && !g.get(f).isEmpty()) {
            String t = g.get(f).remove(g.get(f).size() - 1);
            dfs(t);
        }
        ans.add(f);
    }
}
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class Solution {
public:
    vector<string> findItinerary(vector<vector<string>>& tickets) {
        sort(tickets.rbegin(), tickets.rend());
        unordered_map<string, vector<string>> g;
        for (const auto& ticket : tickets) {
            g[ticket[0]].push_back(ticket[1]);
        }
        vector<string> ans;
        auto dfs = [&](auto&& dfs, string& f) -> void {
            while (!g[f].empty()) {
                string t = g[f].back();
                g[f].pop_back();
                dfs(dfs, t);
            }
            ans.emplace_back(f);
        };
        string f = "JFK";
        dfs(dfs, f);
        reverse(ans.begin(), ans.end());
        return ans;
    }
};
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func findItinerary(tickets [][]string) (ans []string) {
    sort.Slice(tickets, func(i, j int) bool {
        return tickets[i][0] > tickets[j][0] || (tickets[i][0] == tickets[j][0] && tickets[i][1] > tickets[j][1])
    })
    g := make(map[string][]string)
    for _, ticket := range tickets {
        g[ticket[0]] = append(g[ticket[0]], ticket[1])
    }
    var dfs func(f string)
    dfs = func(f string) {
        for len(g[f]) > 0 {
            t := g[f][len(g[f])-1]
            g[f] = g[f][:len(g[f])-1]
            dfs(t)
        }
        ans = append(ans, f)
    }
    dfs("JFK")
    for i := 0; i < len(ans)/2; i++ {
        ans[i], ans[len(ans)-1-i] = ans[len(ans)-1-i], ans[i]
    }
    return
}
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function findItinerary(tickets: string[][]): string[] {
    const g: Record<string, string[]> = {};
    tickets.sort((a, b) => b[1].localeCompare(a[1]));
    for (const [f, t] of tickets) {
        g[f] = g[f] || [];
        g[f].push(t);
    }
    const ans: string[] = [];
    const dfs = (f: string) => {
        while (g[f] && g[f].length) {
            const t = g[f].pop()!;
            dfs(t);
        }
        ans.push(f);
    };
    dfs('JFK');
    return ans.reverse();
}

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