Givet en sammankopplad och oriktad graf är ett spännande träd i den grafen en subgraf som är ett träd och kopplar samman alla hörn. En enda graf kan ha många olika spännträd. Ett minsta produktspännande träd för en viktad sammankopplad och oriktad graf är ett spännträd med en viktprodukt som är mindre än eller lika med viktprodukten för vartannat spännträd. Viktprodukten av ett spännträd är produkten av vikter som motsvarar varje kant av spännträdet. Alla vikter i den givna grafen kommer att vara positiva för enkelhets skull.
Exempel:
Minimum Product that we can obtain is 180 for above graph by choosing edges 0-1 1-2 0-3 and 1-4
Detta problem kan lösas med hjälp av standard algoritmer för minsta spännträd som Kruskal ( https://www.geeksforgeeks.org/dsa/kruskals-minimum-spanning-tree-algorithm-greedy-algo-2/ )och prim algoritmen men vi måste modifiera vår graf för att använda dessa algoritmer. Minimum spaning tree algoritmer försöker minimera den totala summan av vikter här måste vi minimera den totala produkten av vikter. Vi kan använda egendomen av logaritmer för att övervinna detta problem.
Som vi vet
log(w1* w2 * w3 * …. * wN) = log(w1) + log(w2) + log(w3) ….. + log(wN)
Vi kan ersätta varje vikt av grafen med dess logvärde och sedan tillämpar vi valfri minimum spaning tree-algoritm som kommer att försöka minimera summan av log(wi) vilket i sin tur minimerar viktprodukten.
Till exempel diagram stegen visas nedan diagram
I koden nedan har vi först konstruerat logggrafen från den givna ingångsgrafen, sedan ges den grafen som input till prims MST-algoritm som kommer att minimera den totala summan av vikter av trädet. Eftersom vikterna av den modifierade grafen är logaritmer av den faktiska inmatningsgrafen, minimerar vi faktiskt produkten av vikterna för det spännande trädet.
// A C++ program for getting minimum product // spanning tree The program is for adjacency matrix // representation of the graph #include
// A Java program for getting minimum product // spanning tree The program is for adjacency matrix // representation of the graph import java.util.*; class GFG { // 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[] boolean[] mstSet) { // Initialize min value int min = Integer.MAX_VALUE min_index = 0; 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[] and print Minimum Obtainable // product static void printMST(int parent[] int n int graph[][]) { System.out.printf('Edge Weightn'); int minProduct = 1; for (int i = 1; i < V; i++) { System.out.printf('%d - %d %d n' parent[i] i graph[i][parent[i]]); minProduct *= graph[i][parent[i]]; } System.out.printf('Minimum Obtainable product is %dn' minProduct); } // Function to construct and print MST for a graph // represented using adjacency matrix representation // inputGraph is sent for printing actual edges and // logGraph is sent for actual MST operations static void primMST(int inputGraph[][] double logGraph[][]) { int[] parent = new int[V]; // Array to store constructed MST int[] key = new int[V]; // Key values used to pick minimum // weight edge in cut boolean[] mstSet = new boolean[V]; // To represent set of vertices not // yet included in MST // 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 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++) // logGraph[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 logGraph[u][v] is // smaller than key[v] { if (logGraph[u][v] > 0 && mstSet[v] == false && logGraph[u][v] < key[v]) { parent[v] = u; key[v] = (int)logGraph[u][v]; } } } // print the constructed MST printMST(parent V inputGraph); } // Method to get minimum product spanning tree static void minimumProductMST(int graph[][]) { double[][] logGraph = new double[V][V]; // Constructing logGraph from original graph for (int i = 0; i < V; i++) { for (int j = 0; j < V; j++) { if (graph[i][j] > 0) { logGraph[i][j] = Math.log(graph[i][j]); } else { logGraph[i][j] = 0; } } } // Applying standard Prim's MST algorithm on // Log graph. primMST(graph logGraph); } // Driver code public static void main(String[] args) { /* Let us create the following graph 2 3 (0)--(1)--(2) | / | 6| 8/ 5 |7 | / | (3)-------(4) 9 */ int 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 } }; // Print the solution minimumProductMST(graph); } } // This code has been contributed by 29AjayKumar
# A Python3 program for getting minimum # product spanning tree The program is # for adjacency matrix representation # of the graph import math # Number of vertices in the graph V = 5 # A utility function to find the vertex # with minimum key value from the set # of vertices not yet included in MST def minKey(key mstSet): # Initialize min value min = 10000000 min_index = 0 for v in range(V): if (mstSet[v] == False and key[v] < min): min = key[v] min_index = v return min_index # A utility function to print the constructed # MST stored in parent[] and print Minimum # Obtainable product def printMST(parent n graph): print('Edge Weight') minProduct = 1 for i in range(1 V): print('{} - {} {} '.format(parent[i] i graph[i][parent[i]])) minProduct *= graph[i][parent[i]] print('Minimum Obtainable product is {}'.format( minProduct)) # Function to construct and print MST for # a graph represented using adjacency # matrix representation inputGraph is # sent for printing actual edges and # logGraph is sent for actual MST # operations def primMST(inputGraph logGraph): # Array to store constructed MST parent = [0 for i in range(V)] # Key values used to pick minimum key = [10000000 for i in range(V)] # weight edge in cut # To represent set of vertices not mstSet = [False for i in range(V)] # Yet included in MST # Always include first 1st vertex in MST # Make key 0 so that this vertex is key[0] = 0 # Picked as first vertex # First node is always root of MST parent[0] = -1 # The MST will have V vertices for count in range(0 V - 1): # Pick the minimum key vertex from # the set of vertices not yet # included in MST 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 v in range(V): # logGraph[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 logGraph[u][v] is # smaller than key[v] if (logGraph[u][v] > 0 and mstSet[v] == False and logGraph[u][v] < key[v]): parent[v] = u key[v] = logGraph[u][v] # Print the constructed MST printMST(parent V inputGraph) # Method to get minimum product spanning tree def minimumProductMST(graph): logGraph = [[0 for j in range(V)] for i in range(V)] # Constructing logGraph from # original graph for i in range(V): for j in range(V): if (graph[i][j] > 0): logGraph[i][j] = math.log(graph[i][j]) else: logGraph[i][j] = 0 # Applying standard Prim's MST algorithm # on Log graph. primMST(graph logGraph) # Driver code if __name__=='__main__': ''' Let us create the following graph 2 3 (0)--(1)--(2) | / | 6| 8/ 5 |7 | / | (3)-------(4) 9 ''' 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 ] ] # Print the solution minimumProductMST(graph) # This code is contributed by rutvik_56
// C# program for getting minimum product // spanning tree The program is for adjacency matrix // representation of the graph using System; class GFG { // 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 Boolean[] mstSet) { // Initialize min value int min = int.MaxValue min_index = 0; 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[] and print Minimum Obtainable // product static void printMST(int[] parent int n int[ ] graph) { Console.Write('Edge Weightn'); int minProduct = 1; for (int i = 1; i < V; i++) { Console.Write('{0} - {1} {2} n' parent[i] i graph[i parent[i]]); minProduct *= graph[i parent[i]]; } Console.Write('Minimum Obtainable product is {0}n' minProduct); } // Function to construct and print MST for a graph // represented using adjacency matrix representation // inputGraph is sent for printing actual edges and // logGraph is sent for actual MST operations static void primMST(int[ ] inputGraph double[ ] logGraph) { int[] parent = new int[V]; // Array to store constructed MST int[] key = new int[V]; // Key values used to pick minimum // weight edge in cut Boolean[] mstSet = new Boolean[V]; // To represent set of vertices not // yet included in MST // 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. 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 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++) // logGraph[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 logGraph[u v] is // smaller than key[v] { if (logGraph[u v] > 0 && mstSet[v] == false && logGraph[u v] < key[v]) { parent[v] = u; key[v] = (int)logGraph[u v]; } } } // print the constructed MST printMST(parent V inputGraph); } // Method to get minimum product spanning tree static void minimumProductMST(int[ ] graph) { double[ ] logGraph = new double[V V]; // Constructing logGraph from original graph for (int i = 0; i < V; i++) { for (int j = 0; j < V; j++) { if (graph[i j] > 0) { logGraph[i j] = Math.Log(graph[i j]); } else { logGraph[i j] = 0; } } } // Applying standard Prim's MST algorithm on // Log graph. primMST(graph logGraph); } // Driver code public static void Main(String[] args) { /* Let us create the following graph 2 3 (0)--(1)--(2) | / | 6| 8/ 5 |7 | / | (3)-------(4) 9 */ int[ ] 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 } }; // Print the solution minimumProductMST(graph); } } /* This code contributed by PrinciRaj1992 */
<script> // A Javascript program for getting minimum product // spanning tree The program is for adjacency matrix // representation of the graph // Number of vertices in the graph let V = 5; // A utility function to find the vertex with minimum // key value from the set of vertices not yet included // in MST function minKey(keymstSet) { // Initialize min value let min = Number.MAX_VALUE min_index = 0; for (let 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[] and print Minimum Obtainable // product function printMST(parentngraph) { document.write('Edge Weight
'); let minProduct = 1; for (let i = 1; i < V; i++) { document.write( parent[i]+' - '+ i+' ' +graph[i][parent[i]]+'
'); minProduct *= graph[i][parent[i]]; } document.write('Minimum Obtainable product is ' minProduct+'
'); } // Function to construct and print MST for a graph // represented using adjacency matrix representation // inputGraph is sent for printing actual edges and // logGraph is sent for actual MST operations function primMST(inputGraphlogGraph) { let parent = new Array(V); // Array to store constructed MST let key = new Array(V); // Key values used to pick minimum // weight edge in cut let mstSet = new Array(V); // To represent set of vertices not // yet included in MST // Initialize all keys as INFINITE for (let i = 0; i < V; i++) { key[i] = Number.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 (let count = 0; count < V - 1; count++) { // Pick the minimum key vertex from the set of // vertices not yet included in MST let 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 (let v = 0; v < V; v++) // logGraph[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 logGraph[u][v] is // smaller than key[v] { if (logGraph[u][v] > 0 && mstSet[v] == false && logGraph[u][v] < key[v]) { parent[v] = u; key[v] = logGraph[u][v]; } } } // print the constructed MST printMST(parent V inputGraph); } // Method to get minimum product spanning tree function minimumProductMST(graph) { let logGraph = new Array(V); // Constructing logGraph from original graph for (let i = 0; i < V; i++) { logGraph[i]=new Array(V); for (let j = 0; j < V; j++) { if (graph[i][j] > 0) { logGraph[i][j] = Math.log(graph[i][j]); } else { logGraph[i][j] = 0; } } } // Applying standard Prim's MST algorithm on // Log graph. primMST(graph logGraph); } // Driver code /* Let us create the following graph 2 3 (0)--(1)--(2) | / | 6| 8/ 5 |7 | / | (3)-------(4) 9 */ let 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 ] ]; // Print the solution minimumProductMST(graph); // This code is contributed by rag2127 </script>
Produktion:
Edge Weight 0 - 1 2 1 - 2 3 0 - 3 6 1 - 4 5 Minimum Obtainable product is 180
De tidskomplexitet av denna algoritm är O(V2) eftersom det finns två kapslade för loopar som itererar över alla hörn.
De rymdkomplexitet av denna algoritm är O(V2) eftersom vi använder en 2D-matris av storleken V x V för att lagra ingångsgrafen.