We have discussed Kruskal’s algorithm for Minimum Spanning Tree. Like Kruskal’s algorithm, Prim’s algorithm is also a Greedy algorithm. It starts with an empty spanning tree. The idea is to maintain two sets of vertices. The first set contains the vertices already included in the MST, the other set contains the vertices not yet included. At every step, it considers all the edges that connect the two sets, and picks the minimum weight edge from these edges. After picking the edge, it moves the other endpoint of the edge to the set containing MST.

A group of edges that connects two set of vertices in a graph is called cut in graph theory. *So, at every step of Prim’s algorithm, we find a cut (of two sets, one contains the vertices already included in MST and other contains rest of the verices), pick the minimum weight edge from the cut and include this vertex to MST Set (the set that contains already included vertices).*

** How does Prim’s Algorithm Work?** The idea behind Prim’s algorithm is simple, a spanning tree means all vertices must be connected. So the two disjoint subsets (discussed above) of vertices must be connected to make a

*Spanning*Tree. And they must be connected with the minimum weight edge to make it a

*Minimum*Spanning Tree.

*Algorithm*

**1)** Create a set *mstSet* that keeps track of vertices already included in MST.

**2)** Assign a key value to all vertices in the input graph. Initialize all key values as INFINITE. Assign key value as 0 for the first vertex so that it is picked first.

**3)** While mstSet doesn’t include all vertices

….**a)** Pick a vertex *u* which is not there in *mstSet *and has minimum key value.

….**b)** Include *u *to mstSet.

….**c)** Update key value of all adjacent vertices of *u*. To update the key values, iterate through all adjacent vertices. For every adjacent vertex *v*, if weight of edge *u-v* is less than the previous key value of *v*, update the key value as weight of *u-v*

The idea of using key values is to pick the minimum weight edge from cut. The key values are used only for vertices which are not yet included in MST, the key value for these vertices indicate the minimum weight edges connecting them to the set of vertices included in MST.

Let us understand with the following example:

The set *mstSet *is initially empty and keys assigned to vertices are {0, INF, INF, INF, INF, INF, INF, INF} where INF indicates infinite. Now pick the vertex with minimum key value. The vertex 0 is picked, include it in *mstSet*. So *mstSet *becomes {0}. After including to *mstSet*, update key values of adjacent vertices. Adjacent vertices of 0 are 1 and 7. The key values of 1 and 7 are updated as 4 and 8. Following subgraph shows vertices and their key values, only the vertices with finite key values are shown. The vertices included in MST are shown in green color.

Pick the vertex with minimum key value and not already included in MST (not in mstSET). The vertex 1 is picked and added to mstSet. So mstSet now becomes {0, 1}. Update the key values of adjacent vertices of 1. The key value of vertex 2 becomes 8.

Pick the vertex with minimum key value and not already included in MST (not in mstSET). We can either pick vertex 7 or vertex 2, let vertex 7 is picked. So mstSet now becomes {0, 1, 7}. Update the key values of adjacent vertices of 7. The key value of vertex 6 and 8 becomes finite (1 and 7 respectively).

Pick the vertex with minimum key value and not already included in MST (not in mstSET). Vertex 6 is picked. So mstSet now becomes {0, 1, 7, 6}. Update the key values of adjacent vertices of 6. The key value of vertex 5 and 8 are updated.

We repeat the above steps until *mstSet * includes all vertices of given graph. Finally, we get the following graph.

*How to implement the above algorithm?*

We use a boolean array mstSet[] to represent the set of vertices included in MST. If a value mstSet[v] is true, then vertex v is included in MST, otherwise not. Array key[] is used to store key values of all vertices. Another array parent[] to store indexes of parent nodes in MST. The parent array is the output array which is used to show the constructed MST.

## C/C++

`// A C / C++ program for Prim's Minimum ` `// Spanning Tree (MST) algorithm. The program is ` `// for adjacency matrix representation of the graph ` `#include <stdio.h> ` `#include <limits.h> ` `#include<stdbool.h> ` `// Number of vertices in the graph ` `#define V 5 ` ` ` `// A utility function to find the vertex with ` `// minimum key value, from the set of vertices ` `// not yet included in MST ` `int` `minKey(` `int` `key[], ` `bool` `mstSet[]) ` `{ ` `// Initialize min value ` `int` `min = INT_MAX, min_index; ` ` ` `for` `(` `int` `v = 0; v < V; v++) ` ` ` `if` `(mstSet[v] == ` `false` `&& key[v] < min) ` ` ` `min = key[v], min_index = v; ` ` ` `return` `min_index; ` `} ` ` ` `// A utility function to print the ` `// constructed MST stored in parent[] ` `int` `printMST(` `int` `parent[], ` `int` `n, ` `int` `graph[V][V]) ` `{ ` `printf` `(` `"Edge \tWeight\n"` `); ` `for` `(` `int` `i = 1; i < V; i++) ` ` ` `printf` `(` `"%d - %d \t%d \n"` `, parent[i], i, graph[i][parent[i]]); ` `} ` ` ` `// Function to construct and print MST for ` `// a graph represented using adjacency ` `// matrix representation ` `void` `primMST(` `int` `graph[V][V]) ` `{ ` ` ` `// Array to store constructed MST ` ` ` `int` `parent[V]; ` ` ` `// Key values used to pick minimum weight edge in cut ` ` ` `int` `key[V]; ` ` ` `// To represent set of vertices not yet included in MST ` ` ` `bool` `mstSet[V]; ` ` ` ` ` `// Initialize all keys as INFINITE ` ` ` `for` `(` `int` `i = 0; i < V; i++) ` ` ` `key[i] = INT_MAX, mstSet[i] = ` `false` `; ` ` ` ` ` `// Always include first 1st vertex in MST. ` ` ` `// Make key 0 so that this vertex is picked as first vertex. ` ` ` `key[0] = 0; ` ` ` `parent[0] = -1; ` `// First node is always root of MST ` ` ` ` ` `// The MST will have V vertices ` ` ` `for` `(` `int` `count = 0; count < V-1; count++) ` ` ` `{ ` ` ` `// Pick the minimum key vertex from the ` ` ` `// set of vertices not yet included in MST ` ` ` `int` `u = minKey(key, mstSet); ` ` ` ` ` `// Add the picked vertex to the MST Set ` ` ` `mstSet[u] = ` `true` `; ` ` ` ` ` `// Update key value and parent index of ` ` ` `// the adjacent vertices of the picked vertex. ` ` ` `// Consider only those vertices which are not ` ` ` `// yet included in MST ` ` ` `for` `(` `int` `v = 0; v < V; v++) ` ` ` ` ` `// graph[u][v] is non zero only for adjacent vertices of m ` ` ` `// mstSet[v] is false for vertices not yet included in MST ` ` ` `// Update the key only if graph[u][v] is smaller than key[v] ` ` ` `if` `(graph[u][v] && mstSet[v] == ` `false` `&& graph[u][v] < key[v]) ` ` ` `parent[v] = u, key[v] = graph[u][v]; ` ` ` `} ` ` ` ` ` `// print the constructed MST ` ` ` `printMST(parent, V, graph); ` `} ` ` ` ` ` `// driver program to test above function ` `int` `main() ` `{ ` `/* Let us create the following graph ` ` ` `2 3 ` ` ` `(0)--(1)--(2) ` ` ` `| / \ | ` ` ` `6| 8/ \5 |7 ` ` ` `| / \ | ` ` ` `(3)-------(4) ` ` ` `9 */` `int` `graph[V][V] = {{0, 2, 0, 6, 0}, ` ` ` `{2, 0, 3, 8, 5}, ` ` ` `{0, 3, 0, 0, 7}, ` ` ` `{6, 8, 0, 0, 9}, ` ` ` `{0, 5, 7, 9, 0}}; ` ` ` ` ` `// Print the solution ` ` ` `primMST(graph); ` ` ` ` ` `return` `0; ` `} ` |

*chevron_right*

*filter_none*

## Java

`// A Java program for Prim's Minimum Spanning Tree (MST) algorithm. ` `// The program is for adjacency matrix representation of the graph ` ` ` `import` `java.util.*; ` `import` `java.lang.*; ` `import` `java.io.*; ` ` ` `class` `MST ` `{ ` ` ` `// Number of vertices in the graph ` ` ` `private` `static` `final` `int` `V=` `5` `; ` ` ` ` ` `// A utility function to find the vertex with minimum key ` ` ` `// value, from the set of vertices not yet included in MST ` ` ` `int` `minKey(` `int` `key[], Boolean mstSet[]) ` ` ` `{ ` ` ` `// Initialize min value ` ` ` `int` `min = Integer.MAX_VALUE, min_index=-` `1` `; ` ` ` ` ` `for` `(` `int` `v = ` `0` `; v < V; v++) ` ` ` `if` `(mstSet[v] == ` `false` `&& key[v] < min) ` ` ` `{ ` ` ` `min = key[v]; ` ` ` `min_index = v; ` ` ` `} ` ` ` ` ` `return` `min_index; ` ` ` `} ` ` ` ` ` `// A utility function to print the constructed MST stored in ` ` ` `// parent[] ` ` ` `void` `printMST(` `int` `parent[], ` `int` `n, ` `int` `graph[][]) ` ` ` `{ ` ` ` `System.out.println(` `"Edge \tWeight"` `); ` ` ` `for` `(` `int` `i = ` `1` `; i < V; i++) ` ` ` `System.out.println(parent[i]+` `" - "` `+ i+` `"\t"` `+ ` ` ` `graph[i][parent[i]]); ` ` ` `} ` ` ` ` ` `// Function to construct and print MST for a graph represented ` ` ` `// using adjacency matrix representation ` ` ` `void` `primMST(` `int` `graph[][]) ` ` ` `{ ` ` ` `// Array to store constructed MST ` ` ` `int` `parent[] = ` `new` `int` `[V]; ` ` ` ` ` `// Key values used to pick minimum weight edge in cut ` ` ` `int` `key[] = ` `new` `int` `[V]; ` ` ` ` ` `// To represent set of vertices not yet included in MST ` ` ` `Boolean mstSet[] = ` `new` `Boolean[V]; ` ` ` ` ` `// Initialize all keys as INFINITE ` ` ` `for` `(` `int` `i = ` `0` `; i < V; i++) ` ` ` `{ ` ` ` `key[i] = Integer.MAX_VALUE; ` ` ` `mstSet[i] = ` `false` `; ` ` ` `} ` ` ` ` ` `// Always include first 1st vertex in MST. ` ` ` `key[` `0` `] = ` `0` `; ` `// Make key 0 so that this vertex is ` ` ` `// picked as first vertex ` ` ` `parent[` `0` `] = -` `1` `; ` `// First node is always root of MST ` ` ` ` ` `// The MST will have V vertices ` ` ` `for` `(` `int` `count = ` `0` `; count < V-` `1` `; count++) ` ` ` `{ ` ` ` `// Pick thd minimum key vertex from the set of vertices ` ` ` `// not yet included in MST ` ` ` `int` `u = minKey(key, mstSet); ` ` ` ` ` `// Add the picked vertex to the MST Set ` ` ` `mstSet[u] = ` `true` `; ` ` ` ` ` `// Update key value and parent index of the adjacent ` ` ` `// vertices of the picked vertex. Consider only those ` ` ` `// vertices which are not yet included in MST ` ` ` `for` `(` `int` `v = ` `0` `; v < V; v++) ` ` ` ` ` `// graph[u][v] is non zero only for adjacent vertices of m ` ` ` `// mstSet[v] is false for vertices not yet included in MST ` ` ` `// Update the key only if graph[u][v] is smaller than key[v] ` ` ` `if` `(graph[u][v]!=` `0` `&& mstSet[v] == ` `false` `&& ` ` ` `graph[u][v] < key[v]) ` ` ` `{ ` ` ` `parent[v] = u; ` ` ` `key[v] = graph[u][v]; ` ` ` `} ` ` ` `} ` ` ` ` ` `// print the constructed MST ` ` ` `printMST(parent, V, graph); ` ` ` `} ` ` ` ` ` `public` `static` `void` `main (String[] args) ` ` ` `{ ` ` ` `/* Let us create the following graph ` ` ` `2 3 ` ` ` `(0)--(1)--(2) ` ` ` `| / \ | ` ` ` `6| 8/ \5 |7 ` ` ` `| / \ | ` ` ` `(3)-------(4) ` ` ` `9 */` ` ` `MST t = ` `new` `MST(); ` ` ` `int` `graph[][] = ` `new` `int` `[][] {{` `0` `, ` `2` `, ` `0` `, ` `6` `, ` `0` `}, ` ` ` `{` `2` `, ` `0` `, ` `3` `, ` `8` `, ` `5` `}, ` ` ` `{` `0` `, ` `3` `, ` `0` `, ` `0` `, ` `7` `}, ` ` ` `{` `6` `, ` `8` `, ` `0` `, ` `0` `, ` `9` `}, ` ` ` `{` `0` `, ` `5` `, ` `7` `, ` `9` `, ` `0` `}}; ` ` ` ` ` `// Print the solution ` ` ` `t.primMST(graph); ` ` ` `} ` `} ` `// This code is contributed by Aakash Hasija ` |

*chevron_right*

*filter_none*

## Python

`# A Python program for Prim's Minimum Spanning Tree (MST) algorithm. ` `# The program is for adjacency matrix representation of the graph ` ` ` `import` `sys ` `# Library for INT_MAX ` ` ` `class` `Graph(): ` ` ` ` ` `def` `__init__(` `self` `, vertices): ` ` ` `self` `.V ` `=` `vertices ` ` ` `self` `.graph ` `=` `[[` `0` `for` `column ` `in` `range` `(vertices)] ` ` ` `for` `row ` `in` `range` `(vertices)] ` ` ` ` ` `# A utility function to print the constructed MST stored in parent[] ` ` ` `def` `printMST(` `self` `, parent): ` ` ` `print` `"Edge \tWeight"` ` ` `for` `i ` `in` `range` `(` `1` `,` `self` `.V): ` ` ` `print` `parent[i],` `"-"` `,i,` `"\t"` `,` `self` `.graph[i][ parent[i] ] ` ` ` ` ` `# A utility function to find the vertex with ` ` ` `# minimum distance value, from the set of vertices ` ` ` `# not yet included in shortest path tree ` ` ` `def` `minKey(` `self` `, key, mstSet): ` ` ` ` ` `# Initilaize min value ` ` ` `min` `=` `sys.maxint ` ` ` ` ` `for` `v ` `in` `range` `(` `self` `.V): ` ` ` `if` `key[v] < ` `min` `and` `mstSet[v] ` `=` `=` `False` `: ` ` ` `min` `=` `key[v] ` ` ` `min_index ` `=` `v ` ` ` ` ` `return` `min_index ` ` ` ` ` `# Function to construct and print MST for a graph ` ` ` `# represented using adjacency matrix representation ` ` ` `def` `primMST(` `self` `): ` ` ` ` ` `#Key values used to pick minimum weight edge in cut ` ` ` `key ` `=` `[sys.maxint] ` `*` `self` `.V ` ` ` `parent ` `=` `[` `None` `] ` `*` `self` `.V ` `# Array to store constructed MST ` ` ` `# Make key 0 so that this vertex is picked as first vertex ` ` ` `key[` `0` `] ` `=` `0` ` ` `mstSet ` `=` `[` `False` `] ` `*` `self` `.V ` ` ` ` ` `parent[` `0` `] ` `=` `-` `1` `# First node is always the root of ` ` ` ` ` `for` `cout ` `in` `range` `(` `self` `.V): ` ` ` ` ` `# Pick the minimum distance vertex from ` ` ` `# the set of vertices not yet processed. ` ` ` `# u is always equal to src in first iteration ` ` ` `u ` `=` `self` `.minKey(key, mstSet) ` ` ` ` ` `# Put the minimum distance vertex in ` ` ` `# the shortest path tree ` ` ` `mstSet[u] ` `=` `True` ` ` ` ` `# Update dist value of the adjacent vertices ` ` ` `# of the picked vertex only if the current ` ` ` `# distance is greater than new distance and ` ` ` `# the vertex in not in the shotest path tree ` ` ` `for` `v ` `in` `range` `(` `self` `.V): ` ` ` `# graph[u][v] is non zero only for adjacent vertices of m ` ` ` `# mstSet[v] is false for vertices not yet included in MST ` ` ` `# Update the key only if graph[u][v] is smaller than key[v] ` ` ` `if` `self` `.graph[u][v] > ` `0` `and` `mstSet[v] ` `=` `=` `False` `and` `key[v] > ` `self` `.graph[u][v]: ` ` ` `key[v] ` `=` `self` `.graph[u][v] ` ` ` `parent[v] ` `=` `u ` ` ` ` ` `self` `.printMST(parent) ` ` ` `g ` `=` `Graph(` `5` `) ` `g.graph ` `=` `[ [` `0` `, ` `2` `, ` `0` `, ` `6` `, ` `0` `], ` ` ` `[` `2` `, ` `0` `, ` `3` `, ` `8` `, ` `5` `], ` ` ` `[` `0` `, ` `3` `, ` `0` `, ` `0` `, ` `7` `], ` ` ` `[` `6` `, ` `8` `, ` `0` `, ` `0` `, ` `9` `], ` ` ` `[` `0` `, ` `5` `, ` `7` `, ` `9` `, ` `0` `]] ` ` ` `g.primMST(); ` ` ` `# Contributed by Divyanshu Mehta ` |

*chevron_right*

*filter_none*

## C#

`// A C# program for Prim's Minimum ` `// Spanning Tree (MST) algorithm. ` `// The program is for adjacency ` `// matrix representation of the graph ` `using` `System; ` `class` `MST { ` ` ` ` ` `// Number of vertices in the graph ` ` ` `static` `int` `V = 5; ` ` ` ` ` `// A utility function to find ` ` ` `// the vertex with minimum key ` ` ` `// value, from the set of vertices ` ` ` `// not yet included in MST ` ` ` `static` `int` `minKey(` `int` `[]key, ` `bool` `[]mstSet) ` ` ` `{ ` ` ` ` ` `// Initialize min value ` ` ` `int` `min = ` `int` `.MaxValue, min_index = -1; ` ` ` ` ` `for` `(` `int` `v = 0; v < V; v++) ` ` ` `if` `(mstSet[v] == ` `false` `&& key[v] < min) ` ` ` `{ ` ` ` `min = key[v]; ` ` ` `min_index = v; ` ` ` `} ` ` ` ` ` `return` `min_index; ` ` ` `} ` ` ` ` ` `// A utility function to print ` ` ` `// the constructed MST stored in ` ` ` `// parent[] ` ` ` `static` `void` `printMST(` `int` `[]parent, ` `int` `n, ` `int` `[,]graph) ` ` ` `{ ` ` ` `Console.WriteLine(` `"Edge \tWeight"` `); ` ` ` `for` `(` `int` `i = 1; i < V; i++) ` ` ` `Console.WriteLine(parent[i]+` `" - "` `+ i+` `"\t"` `+ ` ` ` `graph[i,parent[i]]); ` ` ` `} ` ` ` ` ` `// Function to construct and ` ` ` `// print MST for a graph represented ` ` ` `// using adjacency matrix representation ` ` ` `static` `void` `primMST(` `int` `[,]graph) ` ` ` `{ ` ` ` ` ` `// Array to store constructed MST ` ` ` `int` `[]parent = ` `new` `int` `[V]; ` ` ` ` ` `// Key values used to pick ` ` ` `// minimum weight edge in cut ` ` ` `int` `[]key = ` `new` `int` `[V]; ` ` ` ` ` `// To represent set of vertices ` ` ` `// not yet included in MST ` ` ` `bool` `[]mstSet = ` `new` `bool` `[V]; ` ` ` ` ` `// Initialize all keys ` ` ` `// as INFINITE ` ` ` `for` `(` `int` `i = 0; i < V; i++) ` ` ` `{ ` ` ` `key[i] = ` `int` `.MaxValue; ` ` ` `mstSet[i] = ` `false` `; ` ` ` `} ` ` ` ` ` `// Always include first 1st vertex in MST. ` ` ` `// Make key 0 so that this vertex is ` ` ` `// picked as first vertex ` ` ` `// First node is always root of MST ` ` ` `key[0] = 0; ` ` ` `parent[0] = -1; ` ` ` ` ` `// The MST will have V vertices ` ` ` `for` `(` `int` `count = 0; count < V - 1; count++) ` ` ` `{ ` ` ` ` ` `// Pick thd minimum key vertex ` ` ` `// from the set of vertices ` ` ` `// not yet included in MST ` ` ` `int` `u = minKey(key, mstSet); ` ` ` ` ` `// Add the picked vertex ` ` ` `// to the MST Set ` ` ` `mstSet[u] = ` `true` `; ` ` ` ` ` `// Update key value and parent ` ` ` `// index of the adjacent vertices ` ` ` `// of the picked vertex. Consider ` ` ` `// only those vertices which are ` ` ` `// not yet included in MST ` ` ` `for` `(` `int` `v = 0; v < V; v++) ` ` ` ` ` `// graph[u][v] is non zero only ` ` ` `// for adjacent vertices of m ` ` ` `// mstSet[v] is false for vertices ` ` ` `// not yet included in MST Update ` ` ` `// the key only if graph[u][v] is ` ` ` `// smaller than key[v] ` ` ` `if` `(graph[u,v] != 0 && mstSet[v] == ` `false` `&& ` ` ` `graph[u,v] < key[v]) ` ` ` `{ ` ` ` `parent[v] = u; ` ` ` `key[v] = graph[u,v]; ` ` ` `} ` ` ` `} ` ` ` ` ` `// print the constructed MST ` ` ` `printMST(parent, V, graph); ` ` ` `} ` ` ` ` ` `// Driver Code ` ` ` `public` `static` `void` `Main () ` ` ` `{ ` ` ` ` ` `/* Let us create the following graph ` ` ` `2 3 ` ` ` `(0)--(1)--(2) ` ` ` `| / \ | ` ` ` `6| 8/ \5 |7 ` ` ` `| / \ | ` ` ` `(3)-------(4) ` ` ` `9 */` ` ` ` ` `int` `[,]graph = ` `new` `int` `[,] {{0, 2, 0, 6, 0}, ` ` ` `{2, 0, 3, 8, 5}, ` ` ` `{0, 3, 0, 0, 7}, ` ` ` `{6, 8, 0, 0, 9}, ` ` ` `{0, 5, 7, 9, 0}}; ` ` ` ` ` `// Print the solution ` ` ` `primMST(graph); ` ` ` `} ` `} ` ` ` `// This code is contributed by anuj_67. ` |

*chevron_right*

*filter_none*

Output:

Edge Weight 0 - 1 2 1 - 2 3 0 - 3 6 1 - 4 5

Time Complexity of the above program is O(V^2). If the input graph is represented using adjacency list, then the time complexity of Prim’s algorithm can be reduced to O(E log V) with the help of binary heap. Please see Prim’s MST for Adjacency List Representation for more details.

Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.

## Recommended Posts:

- Kruskal’s Minimum Spanning Tree Algorithm | Greedy Algo-2
- Kruskal's Minimum Spanning Tree using STL in C++
- Minimum Product Spanning Tree
- Applications of Minimum Spanning Tree Problem
- Boruvka's algorithm for Minimum Spanning Tree
- Reverse Delete Algorithm for Minimum Spanning Tree
- Maximum Possible Edge Disjoint Spanning Tree From a Complete Graph
- Problem Solving for Minimum Spanning Trees (Kruskal’s and Prim’s)
- Greedy Algorithm to find Minimum number of Coins
- Minimum Operations to make value of all vertices of the tree Zero
- Roots of a tree which give minimum height
- Total number of Spanning Trees in a Graph
- Total number of Spanning trees in a Cycle Graph
- Correctness of Greedy Algorithms
- Huffman Coding | Greedy Algo-3