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2203. Minimum Weighted Subgraph With the Required Paths 👍

  • Time: $O(|V|\log |E|)$
  • Space: $O(n)$
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class Solution {
 public:
  long long minimumWeight(int n, vector<vector<int>>& edges, int src1, int src2,
                          int dest) {
    vector<vector<pair<int, int>>> graph(n);
    vector<vector<pair<int, int>>> reversedGraph(n);

    for (const vector<int>& edge : edges) {
      const int u = edge[0];
      const int v = edge[1];
      const int w = edge[2];
      graph[u].emplace_back(v, w);
      reversedGraph[v].emplace_back(u, w);
    }

    const vector<long> fromSrc1 = dijkstra(graph, src1);
    const vector<long> fromSrc2 = dijkstra(graph, src2);
    const vector<long> fromDest = dijkstra(reversedGraph, dest);
    long ans = kMax;

    for (int i = 0; i < n; ++i) {
      if (fromSrc1[i] == kMax || fromSrc2[i] == kMax || fromDest[i] == kMax)
        continue;
      ans = min(ans, fromSrc1[i] + fromSrc2[i] + fromDest[i]);
    }

    return ans == kMax ? -1 : ans;
  }

 private:
  static constexpr long kMax = 10'000'000'000;

  vector<long> dijkstra(const vector<vector<pair<int, int>>>& graph, int src) {
    vector<long> dist(graph.size(), kMax);

    dist[src] = 0;
    using P = pair<long, int>;  // (d, u)
    priority_queue<P, vector<P>, greater<>> minHeap;
    minHeap.emplace(dist[src], src);

    while (!minHeap.empty()) {
      const auto [d, u] = minHeap.top();
      minHeap.pop();
      if (d > dist[u])
        continue;
      for (const auto& [v, w] : graph[u])
        if (d + w < dist[v]) {
          dist[v] = d + w;
          minHeap.emplace(dist[v], v);
        }
    }

    return dist;
  }
};

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class Solution {
  public long minimumWeight(int n, int[][] edges, int src1, int src2, int dest) {
    List<Pair<Integer, Integer>>[] graph = new List[n];
    List<Pair<Integer, Integer>>[] reversedGraph = new List[n];

    for (int i = 0; i < n; ++i) {
      graph[i] = new ArrayList<>();
      reversedGraph[i] = new ArrayList<>();
    }

    for (int[] edge : edges) {
      final int u = edge[0];
      final int v = edge[1];
      final int w = edge[2];
      graph[u].add(new Pair<>(v, w));
      reversedGraph[v].add(new Pair<>(u, w));
    }

    long[] fromSrc1 = dijkstra(graph, src1);
    long[] fromSrc2 = dijkstra(graph, src2);
    long[] fromDest = dijkstra(reversedGraph, dest);
    long ans = kMax;

    for (int i = 0; i < n; ++i) {
      if (fromSrc1[i] == kMax || fromSrc2[i] == kMax || fromDest[i] == kMax)
        continue;
      ans = Math.min(ans, fromSrc1[i] + fromSrc2[i] + fromDest[i]);
    }

    return ans == kMax ? -1 : ans;
  }

  private static long kMax = (long) 1e10;

  private long[] dijkstra(List<Pair<Integer, Integer>>[] graph, int src) {
    long[] dist = new long[graph.length];
    Arrays.fill(dist, kMax);

    dist[src] = 0;
    Queue<Pair<Long, Integer>> minHeap = new PriorityQueue<>(Comparator.comparing(Pair::getKey)) {
      {
        offer(new Pair<>(dist[src], src)); // (d, u)
      }
    };

    while (!minHeap.isEmpty()) {
      final long d = minHeap.peek().getKey();
      final int u = minHeap.poll().getValue();
      if (d > dist[u])
        continue;
      for (Pair<Integer, Integer> pair : graph[u]) {
        final int v = pair.getKey();
        final int w = pair.getValue();
        if (d + w < dist[v]) {
          dist[v] = d + w;
          minHeap.offer(new Pair<>(dist[v], v));
        }
      }
    }

    return dist;
  }
}

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class Solution:
  def minimumWeight(
      self,
      n: int,
      edges: list[list[int]],
      src1: int,
      src2: int,
      dest: int,
  ) -> int:
    graph = [[] for _ in range(n)]
    reversedGraph = [[] for _ in range(n)]

    for u, v, w in edges:
      graph[u].append((v, w))
      reversedGraph[v].append((u, w))

    fromSrc1 = self._dijkstra(graph, src1)
    fromSrc2 = self._dijkstra(graph, src2)
    fromDest = self._dijkstra(reversedGraph, dest)
    minWeight = min(a + b + c for a, b, c in zip(fromSrc1, fromSrc2, fromDest))
    return -1 if minWeight == math.inf else minWeight

  def _dijkstra(
      self,
      graph: list[list[tuple[int, int]]],
      src: int,
  ) -> list[int]:
    dist = [math.inf] * len(graph)

    dist[src] = 0
    minHeap = [(dist[src], src)]  # (d, u)

    while minHeap:
      d, u = heapq.heappop(minHeap)
      if d > dist[u]:
        continue
      for v, w in graph[u]:
        if d + w < dist[v]:
          dist[v] = d + w
          heapq.heappush(minHeap, (dist[v], v))

    return dist