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2050. Parallel Courses III

Description

You are given an integer n, which indicates that there are n courses labeled from 1 to n. You are also given a 2D integer array relations where relations[j] = [prevCoursej, nextCoursej] denotes that course prevCoursej has to be completed before course nextCoursej (prerequisite relationship). Furthermore, you are given a 0-indexed integer array time where time[i] denotes how many months it takes to complete the (i+1)th course.

You must find the minimum number of months needed to complete all the courses following these rules:

  • You may start taking a course at any time if the prerequisites are met.
  • Any number of courses can be taken at the same time.

Return the minimum number of months needed to complete all the courses.

Note: The test cases are generated such that it is possible to complete every course (i.e., the graph is a directed acyclic graph).

 

Example 1:

Input: n = 3, relations = [[1,3],[2,3]], time = [3,2,5]
Output: 8
Explanation: The figure above represents the given graph and the time required to complete each course. 
We start course 1 and course 2 simultaneously at month 0.
Course 1 takes 3 months and course 2 takes 2 months to complete respectively.
Thus, the earliest time we can start course 3 is at month 3, and the total time required is 3 + 5 = 8 months.

Example 2:

Input: n = 5, relations = [[1,5],[2,5],[3,5],[3,4],[4,5]], time = [1,2,3,4,5]
Output: 12
Explanation: The figure above represents the given graph and the time required to complete each course.
You can start courses 1, 2, and 3 at month 0.
You can complete them after 1, 2, and 3 months respectively.
Course 4 can be taken only after course 3 is completed, i.e., after 3 months. It is completed after 3 + 4 = 7 months.
Course 5 can be taken only after courses 1, 2, 3, and 4 have been completed, i.e., after max(1,2,3,7) = 7 months.
Thus, the minimum time needed to complete all the courses is 7 + 5 = 12 months.

 

Constraints:

  • 1 <= n <= 5 * 104
  • 0 <= relations.length <= min(n * (n - 1) / 2, 5 * 104)
  • relations[j].length == 2
  • 1 <= prevCoursej, nextCoursej <= n
  • prevCoursej != nextCoursej
  • All the pairs [prevCoursej, nextCoursej] are unique.
  • time.length == n
  • 1 <= time[i] <= 104
  • The given graph is a directed acyclic graph.

Solutions

Solution 1: Topological Sorting + Dynamic Programming

First, we construct a directed acyclic graph based on the given prerequisite course relationships, perform topological sorting on this graph, and then use dynamic programming to find the minimum time required to complete all courses according to the results of the topological sorting.

We define the following data structures or variables:

  • Adjacency list $g$ stores the directed acyclic graph, and an array $indeg$ stores the in-degree of each node;
  • Queue $q$ stores all nodes with an in-degree of $0$;
  • Array $f$ stores the earliest completion time of each node, initially $f[i] = 0$;
  • Variable $ans$ records the final answer, initially $ans = 0$;

When $q$ is not empty, take out the head node $i$ in turn, traverse each node $j$ in $g[i]$, update $f[j] = \max(f[j], f[i] + time[j])$, update $ans = \max(ans, f[j])$ at the same time, and reduce the in-degree of $j$ by $1$. If the in-degree of $j$ is $0$ at this time, add $j$ to the queue $q$;

Finally, return $ans$.

The time complexity is $O(m + n)$, and the space complexity is $O(m + n)$. Where $m$ is the length of the array $relations$.

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class Solution:
    def minimumTime(self, n: int, relations: List[List[int]], time: List[int]) -> int:
        g = defaultdict(list)
        indeg = [0] * n
        for a, b in relations:
            g[a - 1].append(b - 1)
            indeg[b - 1] += 1
        q = deque()
        f = [0] * n
        ans = 0
        for i, (v, t) in enumerate(zip(indeg, time)):
            if v == 0:
                q.append(i)
                f[i] = t
                ans = max(ans, t)
        while q:
            i = q.popleft()
            for j in g[i]:
                f[j] = max(f[j], f[i] + time[j])
                ans = max(ans, f[j])
                indeg[j] -= 1
                if indeg[j] == 0:
                    q.append(j)
        return ans
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class Solution {
    public int minimumTime(int n, int[][] relations, int[] time) {
        List<Integer>[] g = new List[n];
        Arrays.setAll(g, k -> new ArrayList<>());
        int[] indeg = new int[n];
        for (int[] e : relations) {
            int a = e[0] - 1, b = e[1] - 1;
            g[a].add(b);
            ++indeg[b];
        }
        Deque<Integer> q = new ArrayDeque<>();
        int[] f = new int[n];
        int ans = 0;
        for (int i = 0; i < n; ++i) {
            int v = indeg[i], t = time[i];
            if (v == 0) {
                q.offer(i);
                f[i] = t;
                ans = Math.max(ans, t);
            }
        }
        while (!q.isEmpty()) {
            int i = q.pollFirst();
            for (int j : g[i]) {
                f[j] = Math.max(f[j], f[i] + time[j]);
                ans = Math.max(ans, f[j]);
                if (--indeg[j] == 0) {
                    q.offer(j);
                }
            }
        }
        return ans;
    }
}
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class Solution {
public:
    int minimumTime(int n, vector<vector<