重建行程(最短的歐拉路徑)Reconstruct Itinerary

問題:算法

Given a list of airline tickets represented by pairs of departure and arrival airports [from, to], reconstruct the itinerary in order. All of the tickets belong to a man who departs from JFK. Thus, the itinerary must begin with JFK.api

Note:spa

  1. If there are multiple valid itineraries, you should return the itinerary that has the smallest lexical order when read as a single string. For example, the itinerary ["JFK", "LGA"] has a smaller lexical order than ["JFK", "LGB"].
  2. All airports are represented by three capital letters (IATA code).
  3. You may assume all tickets form at least one valid itinerary.

Example 1:
tickets = [["MUC", "LHR"], ["JFK", "MUC"], ["SFO", "SJC"], ["LHR", "SFO"]]
Return ["JFK", "MUC", "LHR", "SFO", "SJC"].code

Example 2:
tickets = [["JFK","SFO"],["JFK","ATL"],["SFO","ATL"],["ATL","JFK"],["ATL","SFO"]]
Return ["JFK","ATL","JFK","SFO","ATL","SFO"].
Another possible reconstruction is ["JFK","SFO","ATL","JFK","ATL","SFO"]. But it is larger in lexical order.orm

解決:three

① 使用Map+DFS。ip

定義:

   歐拉回路:從圖的某一個頂點出發,圖中每條邊走且僅走一次,最後回到出發點;若是這樣的迴路存在,則稱之爲歐拉回路。 
   歐拉路徑:從圖的某一個頂點出發,圖中每條邊走且僅走一次,最後到達某一個點;若是這樣的路徑存在,則稱之爲歐拉路徑。

判斷:get

     無向圖歐拉回路判斷:全部頂點的度數都爲偶數。string

     有向圖歐拉回路判斷:全部頂點的出度與入讀相等。it

     無向圖歐拉路徑判斷: 至多有兩個頂點的度數爲奇數,其餘頂點的度數爲偶數。

     有向圖歐拉路徑判斷: 至多有兩個頂點的入度和出度絕對值差1(如有兩個這樣的頂點,則必須其中一個出度大於入度,另外一個入度大於出度),其餘頂點的入度與出度相等。

全部機場都是頂點,票據是有向邊。 而後全部這些票造成一個有向圖。

由於咱們知道歐拉路徑存在,因此圖必須是歐拉。

所以,從「JFK」開始,咱們能夠應用Hierholzer算法在圖中找到歐拉路徑,這是一個有效的重構。

因爲問題要求詞法順序最小的解決方案,咱們能夠把鄰居放在一個小堆裏。 經過這種方式,咱們老是先訪問最小的鄰居

class Solution { //10ms     Map<String,PriorityQueue<String>> map = new HashMap<>();     List<String> res = new ArrayList<>();     public List<String> findItinerary(String[][] tickets) {         for (String[] ticket : tickets){             if (! map.containsKey(ticket[0])){                 PriorityQueue<String> queue = new PriorityQueue<>();                 map.put(ticket[0],queue);             }             map.get(ticket[0]).offer(ticket[1]);         }         dfs("JFK");         return res;     }     public void dfs(String s){         PriorityQueue<String> queue = map.get(s);         while(queue != null && ! queue.isEmpty()){             dfs(queue.poll());         }         res.add(0,s);     } } 

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