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Posts tagged as “graph”

花花酱 LeetCode 743. Network Delay Time

There are N network nodes, labelled 1 to N.

Given times, a list of travel times as directed edges times[i] = (u, v, w), where u is the source node, v is the target node, and w is the time it takes for a signal to travel from source to target.

Now, we send a signal from a certain node K. How long will it take for all nodes to receive the signal? If it is impossible, return -1.

Note:

  1. N will be in the range [1, 100].
  2. K will be in the range [1, N].
  3. The length of times will be in the range [1, 6000].
  4. All edges times[i] = (u, v, w) will have 1 <= u, v <= N and 1 <= w <= 100.

Idea:

Construct the graph and do a shortest path from K to all other nodes.

Solution 2:

C++ / Bellman-Ford

Time complexity: O(ne)

Space complexity: O(n)

 

Solution3:

C++ / Floyd-Warshall

Time complexity: O(n^3)

Space complexity: O(n^2)

v2

花花酱 LeetCode 399. Evaluate Division

题目大意:给你一些含有变量名的分式的值,让你计算另外一些分式的值,如果不能计算返回-1。

Problem:

Equations are given in the format A / B = k, where A and B are variables represented as strings, and k is a real number (floating point number). Given some queries, return the answers. If the answer does not exist, return -1.0.

Example:
Given a / b = 2.0, b / c = 3.0.
queries are: a / c = ?, b / a = ?, a / e = ?, a / a = ?, x / x = ? .
return [6.0, 0.5, -1.0, 1.0, -1.0 ].

The input is: vector<pair<string, string>> equations, vector<double>& values, vector<pair<string, string>> queries , where equations.size() == values.size(), and the values are positive. This represents the equations. Return vector<double>.

According to the example above:

The input is always valid. You may assume that evaluating the queries will result in no division by zero and there is no contradiction.

 

Solution 1: DFS

C++

Java

Python3



Solution 2: Union Find

C++

Java

Python3

Related Problems:

花花酱 LeetCode 207. Course Schedule

Problem:

There are a total of n courses you have to take, labeled from 0 to n - 1.

Some courses may have prerequisites, for example to take course 0 you have to first take course 1, which is expressed as a pair: [0,1]

Given the total number of courses and a list of prerequisite pairs, is it possible for you to finish all courses?

For example:

There are a total of 2 courses to take. To take course 1 you should have finished course 0. So it is possible.

There are a total of 2 courses to take. To take course 1 you should have finished course 0, and to take course 0 you should also have finished course 1. So it is impossible.



Idea:

Finding cycles O(n^2) -> Topological sort O(n)

Solution 1: Topological Sort

C++

Java



Solution 2: DFS Finding cycles

Time complexity: O(n^2)

Space complexity: O(n)

C++

Related Pr0blems:

花花酱 LeetCode 126. Word Ladder II

Problem:

Given two words (beginWord and endWord), and a dictionary’s word list, find all shortest transformation sequence(s) from beginWord to endWord, such that:

  1. Only one letter can be changed at a time
  2. Each transformed word must exist in the word list. Note that beginWord is not a transformed word.

For example,

Given:
beginWord = "hit"
endWord = "cog"
wordList = ["hot","dot","dog","lot","log","cog"]

Return

Note:

  • Return an empty list if there is no such transformation sequence.
  • All words have the same length.
  • All words contain only lowercase alphabetic characters.
  • You may assume no duplicates in the word list.
  • You may assume beginWord and endWord are non-empty and are not the same.

Idea:

BFS to construct the graph + DFS to extract the paths



Solutions:

C++, BFS 1


C++ / BFS 2

 

C++ / Bidirectional BFS

 

花花酱 LeetCode 332. Reconstruct Itinerary

Problem:

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.

Note:

  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"].

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.

 

Idea:

Convert the graph to a tree and do post-order traversal

 Solution: