Lexicographically Smallest Topological Ordering

Given a directed graph with N vertices and M edges that may contain cycles, the task is to find the lexicographically smallest topological ordering of the graph if it exists otherwise print -1 (if the graph has cycles).
Lexigraphically smallest topological ordering means that if two vertices in a graph do not have any incoming edge then the vertex with the smaller number should appear first in the ordering.
For Example, in the image below many topological orderings are possible e.g 5 2 3 4 0 1, 5 0 2 4 3 1.
But the smallest ordering is 4 5 0 2 3 1.

Examples:

Input:

Output: 4 5 0 2 3 1
Even though 5 4 0 2 3 1 is also a valid topological
ordering of the given graph but it is not
lexicographically smallest.

Approach: We will use Kahn’s algorithm for Topological Sorting with a modification. Instead of using a queue we will use a multiset to store the vertices to make sure that every time we pick a vertex it is the smallest possible of all. The overall Time complexity changes to O(VlogV+E)

Below is the implementation of the above approach:

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// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
  
// Class to represent a graph
class Graph {
    int V; // No. of vertices'
  
    // Pointer to an array containing
    // adjacency listsList
    list<int>* adj;
  
public:
    Graph(int V); // Constructor
  
    // Function to add an edge to graph
    void addEdge(int u, int v);
  
    // Function to print the required topological
    // sort of the given graph
    void topologicalSort();
};
  
// Constructor
Graph::Graph(int V)
{
    this->V = V;
    adj = new list<int>[V];
}
  
// Function to add an edge to the graph
void Graph::addEdge(int u, int v)
{
    adj[u].push_back(v);
}
  
// Function to print the required topological
// sort of the given graph
void Graph::topologicalSort()
{
    // Create a vector to store indegrees of all
    // the vertices
    // Initialize all indegrees to 0
    vector<int> in_degree(V, 0);
  
    // Traverse adjacency lists to fill indegrees of
    // vertices
    // This step takes O(V+E) time
    for (int u = 0; u < V; u++) {
        list<int>::iterator itr;
        for (itr = adj[u].begin(); itr != adj[u].end(); itr++)
            in_degree[*itr]++;
    }
  
    // Create a set and inserting all vertices with
    // indegree 0
    multiset<int> s;
    for (int i = 0; i < V; i++)
        if (in_degree[i] == 0)
            s.insert(i);
  
    // Initialize count of visited vertices
    int cnt = 0;
  
    // Create a vector to store result (A topological
    // ordering of the vertices)
    vector<int> top_order;
  
    // One by one erase vertices from setand insert
    // adjacents if indegree of adjacent becomes 0
    while (!s.empty()) {
  
        // Extract vertex with minimum number from multiset
        // and add it to topological order
        int u = *s.begin();
        s.erase(s.begin());
        top_order.push_back(u);
  
        // Iterate through all its neighbouring nodes
        // of erased node u and decrease their in-degree
        // by 1
        list<int>::iterator itr;
        for (itr = adj[u].begin(); itr != adj[u].end(); itr++)
  
            // If in-degree becomes zero, add it to queue
            if (--in_degree[*itr] == 0)
                s.insert(*itr);
  
        cnt++;
    }
  
    // Check if there was a cycle
    if (cnt != V) {
        cout << -1;
        return;
    }
  
    // Print topological order
    for (int i = 0; i < top_order.size(); i++)
        cout << top_order[i] << " ";
}
  
// Driver code
int main()
{
    // Create the graph
    Graph g(6);
    g.addEdge(5, 2);
    g.addEdge(5, 0);
    g.addEdge(4, 0);
    g.addEdge(4, 1);
    g.addEdge(2, 3);
    g.addEdge(3, 1);
  
    // Find the required topological order
    g.topologicalSort();
  
    return 0;
}

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Output:


4 5 0 2 3 1





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