Minimum Spanning Tree
1. What is a Spanning Tree?
In an undirected and connected graph G=(V,E), a spanning tree is a subgraph that is a tree which includes all of the vertices of G, with minimum possible number of edges. A graph may have several spanning trees. The cost of the spanning tree is the sum of the weights of all the edges in the tree
2. What is a Minimum Spanning Tree?
A minimum spanning tree (M- ST) is the spanning tree where the cost is minimum among all the spanning trees.
3. Prim’s Algorithm
- Prim’s algorithm is a greedy algorithm that works well on dense graphs.
- It finds a minimum spanning tree for a weighted UNDIRECTED graph.
Algorithm Steps:
- Choose any arbitrary node s as root node
- Enqueues all edges incident to s into a Priority Queue (PQ)
- Repeatedly do the following greedy steps until PQ is empty: If the vertex v with edge e (w -> v) in the PQ has not been visited then add e to MST and enqueue all edges connected to v into the PQ.
Visualising
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57 | #include <iostream>
#include <vector>
#include <queue>
std::vector<std::vector<std::pair<int, int>>> adj;
std::vector<bool> visited;
std::priority_queue<std::pair<int, int>, std::vector<std::pair<int, int>>, std::greater<std::pair<int, int>>> queue;
void addEdges(int s) {
visited[s] = true;
for (int i = 0; i < adj[s].size(); ++i) {
if (visited[adj[s][i].second]) {
continue;
}
queue.push(adj[s][i]);
}
}
int main() {
int n, m, a, b, w;
std::cin >> n >> m;
adj = std::vector<std::vector<std::pair<int, int>>>(n + 1, std::vector<std::pair<int, int>>{});
visited = std::vector<bool>(n + 1, false);
for (int i = 0; i < m; ++i) {
std::cin >> a >> b >> w;
adj[a].push_back(std::make_pair(w, b));
adj[b].push_back(std::make_pair(w, a));
}
int edgeCount = 0;
int mstCost = 0;
addEdges(1);
while(!queue.empty() && edgeCount != n - 1) {
auto cost = queue.top().first;
auto des = queue.top().second;
queue.pop();
if (visited[des]) {
continue;
}
mstCost += cost;
++edgeCount;
addEdges(des);
}
if (edgeCount != n - 1) {
// No MST found
std::cout << "0";
} else {
std::cout << mstCost;
}
}
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The time complexity of Prim's algorithm is O(E log V).
4. Kruskal’s Algorithm
- Kruskal’s algorithm is a greedy algorithm that works well on dense graphs.
Algorithm Steps:
- Sort the set of edges E in increasing order
- Start adding edges to the MST from the edge with the smallest weight until the edge of the largest weight.
- Only add edges which doesn't form a cycle , edges which connect only disconnected components.
So now the question is how to check if vertices are connected or not ?
This could be done using DFS but DFS will make time complexity large. So the best solution is Disjoint Set
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60 | #include <iostream>
#include <vector>
#include <algorithm>
class DisjointSet {
private:
std::vector<int> parents;
public:
DisjointSet(int n) {
parents = std::vector<int>(n + 1, -1);
for (int i = 1; i <= n; ++i) {
parents[i] = i;
}
}
int find(int x) {
while (parents[x] != x) {
parents[x] = parents[parents[x]];
x = parents[x];
}
return parents[x];
}
void unionSet(int x, int y) {
auto parentX = find(x);
auto parentY = find(y);
parents[parentY] = parentX;
}
};
int main() {
int n, m, a, b, w;
std::cin >> n >> m;
std::vector<std::pair<int, std::pair<int, int>>> edges;
for (int i = 0; i < m; ++i) {
std::cin >> a >> b >> w;
edges.push_back(std::make_pair(w, std::make_pair(a, b)));
}
DisjointSet disjointSet(n);
std::sort(edges.begin(), edges.end());
int mst = 0;
for (int i = 0; i < edges.size(); ++i) {
auto cost = edges[i].first;
auto s = edges[i].second.first;
auto d = edges[i].second.second;
if (disjointSet.find(s) != disjointSet.find(d)) {
disjointSet.unionSet(s, d);
mst += cost;
}
}
std::cout << mst << std::endl;
}
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