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Omvänd raderingsalgoritm för minsta spannande träd

Prova det på GfG Practice Omvänd raderingsalgoritm för minsta spannande träd' title= #practiceLinkDiv { display: ingen !viktigt; }

Omvänd raderingsalgoritm är nära relaterad till Kruskals algoritm . I Kruskals algoritm är det vi gör: Sortera kanter genom att öka ordningen på deras vikter. Efter sortering plockar vi en och en kanter i ökande ordning. Vi inkluderar nuvarande plockade kant om genom att inkludera detta i spännträdet inte bildar någon cykel förrän det finns V-1 kanter i spännträdet där V = antal hörn.

I Reverse Delete-algoritmen sorterar vi in ​​alla kanter minskar ordning på deras vikter. Efter sortering plockar vi en och en kanter i fallande ordning. Vi inkludera strömvald flank om exkludering av strömflank orsakar frånkoppling i strömgrafen . Huvudidén är delete edge om raderingen inte leder till att grafen kopplas bort.

array sträng i c

Algoritmen:



  1. Sortera alla kanter på grafen i icke-ökande ordning av kantvikter.
  2. Initiera MST som originalgraf och ta bort extra kanter med steg 3.
  3. Välj högsta vikt kant från återstående kanter och kontrollera om du tar bort kanten kopplar bort grafen   eller inte .
     Om vi ​​kopplar bort tar vi inte bort kanten.
    Annars tar vi bort kanten och fortsätter. 

Illustration:  

Låt oss förstå med följande exempel:

reversedelete2


Om vi ​​tar bort högsta viktkant av vikt 14 kopplas inte grafen bort så vi tar bort den. 
 

reversedelete3' title=


Därefter tar vi bort 11 eftersom borttagningen inte kopplar bort grafen. 
 

reversedelete4' title=


Därefter tar vi bort 10 eftersom borttagningen inte kopplar bort grafen. 
 

reversedelete5' title=


Nästa är 9. Vi kan inte ta bort 9 eftersom borttagning av den orsakar frånkoppling. 
 

' title=


Vi fortsätter på det här sättet och efterkanterna kvarstår i sista MST. 

Edges in MST  
(3 4)
(0 7)
(2 3)
(2 5)
(0 1)
(5 6)
(2 8)
(6 7)

Obs: Vid samma viktkanter kan vi välja valfri kant av samma viktkanter.

Rekommenderad praxis Omvänd raderingsalgoritm för minsta spannande träd Prova!

Genomförande:

C++
// C++ program to find Minimum Spanning Tree // of a graph using Reverse Delete Algorithm #include   using namespace std; // Creating shortcut for an integer pair typedef pair<int int> iPair; // Graph class represents a directed graph // using adjacency list representation class Graph {  int V; // No. of vertices  list<int> *adj;  vector< pair<int iPair> > edges;  void DFS(int v bool visited[]); public:  Graph(int V); // Constructor  // function to add an edge to graph  void addEdge(int u int v int w);  // Returns true if graph is connected  bool isConnected();  void reverseDeleteMST(); }; Graph::Graph(int V) {  this->V = V;  adj = new list<int>[V]; } void Graph::addEdge(int u int v int w) {  adj[u].push_back(v); // Add w to v’s list.  adj[v].push_back(u); // Add w to v’s list.  edges.push_back({w {u v}}); } void Graph::DFS(int v bool visited[]) {  // Mark the current node as visited and print it  visited[v] = true;  // Recur for all the vertices adjacent to  // this vertex  list<int>::iterator i;  for (i = adj[v].begin(); i != adj[v].end(); ++i)  if (!visited[*i])  DFS(*i visited); } // Returns true if given graph is connected else false bool Graph::isConnected() {  bool visited[V];  memset(visited false sizeof(visited));  // Find all reachable vertices from first vertex  DFS(0 visited);  // If set of reachable vertices includes all  // return true.  for (int i=1; i<V; i++)  if (visited[i] == false)  return false;  return true; } // This function assumes that edge (u v) // exists in graph or not void Graph::reverseDeleteMST() {  // Sort edges in increasing order on basis of cost  sort(edges.begin() edges.end());  int mst_wt = 0; // Initialize weight of MST  cout << 'Edges in MSTn';  // Iterate through all sorted edges in  // decreasing order of weights  for (int i=edges.size()-1; i>=0; i--)  {  int u = edges[i].second.first;  int v = edges[i].second.second;  // Remove edge from undirected graph  adj[u].remove(v);  adj[v].remove(u);  // Adding the edge back if removing it  // causes disconnection. In this case this   // edge becomes part of MST.  if (isConnected() == false)  {  adj[u].push_back(v);  adj[v].push_back(u);  // This edge is part of MST  cout << '(' << u << ' ' << v << ') n';  mst_wt += edges[i].first;  }  }  cout << 'Total weight of MST is ' << mst_wt; } // Driver code int main() {  // create the graph given in above figure  int V = 9;  Graph g(V);  // making above shown graph  g.addEdge(0 1 4);  g.addEdge(0 7 8);  g.addEdge(1 2 8);  g.addEdge(1 7 11);  g.addEdge(2 3 7);  g.addEdge(2 8 2);  g.addEdge(2 5 4);  g.addEdge(3 4 9);  g.addEdge(3 5 14);  g.addEdge(4 5 10);  g.addEdge(5 6 2);  g.addEdge(6 7 1);  g.addEdge(6 8 6);  g.addEdge(7 8 7);  g.reverseDeleteMST();  return 0; } 
Java
// Java program to find Minimum Spanning Tree // of a graph using Reverse Delete Algorithm import java.util.*; // class to represent an edge class Edge implements Comparable<Edge> {  int u v w;  Edge(int u int v int w)  {  this.u = u;  this.w = w;  this.v = v;  }  public int compareTo(Edge other)  {  return (this.w - other.w);  } } // Class to represent a graph using adjacency list // representation public class GFG {  private int V; // No. of vertices  private List<Integer>[] adj;  private List<Edge> edges;  @SuppressWarnings({ 'unchecked' 'deprecated' })  public GFG(int v) // Constructor  {  V = v;  adj = new ArrayList[v];  for (int i = 0; i < v; i++)  adj[i] = new ArrayList<Integer>();  edges = new ArrayList<Edge>();  }  // function to Add an edge  public void AddEdge(int u int v int w)  {  adj[u].add(v); // Add w to v’s list.  adj[v].add(u); // Add w to v’s list.  edges.add(new Edge(u v w));  }  // function to perform dfs  private void DFS(int v boolean[] visited)  {  // Mark the current node as visited and print it  visited[v] = true;  // Recur for all the vertices adjacent to  // this vertex  for (int i : adj[v]) {  if (!visited[i])  DFS(i visited);  }  }  // Returns true if given graph is connected else false  private boolean IsConnected()  {  boolean[] visited = new boolean[V];  // Find all reachable vertices from first vertex  DFS(0 visited);  // If set of reachable vertices includes all  // return true.  for (int i = 1; i < V; i++) {  if (visited[i] == false)  return false;  }  return true;  }  // This function assumes that edge (u v)  // exists in graph or not  public void ReverseDeleteMST()  {  // Sort edges in increasing order on basis of cost  Collections.sort(edges);  int mst_wt = 0; // Initialize weight of MST  System.out.println('Edges in MST');  // Iterate through all sorted edges in  // decreasing order of weights  for (int i = edges.size() - 1; i >= 0; i--) {  int u = edges.get(i).u;  int v = edges.get(i).v;  // Remove edge from undirected graph  adj[u].remove(adj[u].indexOf(v));  adj[v].remove(adj[v].indexOf(u));  // Adding the edge back if removing it  // causes disconnection. In this case this  // edge becomes part of MST.  if (IsConnected() == false) {  adj[u].add(v);  adj[v].add(u);  // This edge is part of MST  System.out.println('(' + u + ' ' + v  + ')');  mst_wt += edges.get(i).w;  }  }  System.out.println('Total weight of MST is '  + mst_wt);  }  // Driver code  public static void main(String[] args)  {  // create the graph given in above figure  int V = 9;  GFG g = new GFG(V);  // making above shown graph  g.AddEdge(0 1 4);  g.AddEdge(0 7 8);  g.AddEdge(1 2 8);  g.AddEdge(1 7 11);  g.AddEdge(2 3 7);  g.AddEdge(2 8 2);  g.AddEdge(2 5 4);  g.AddEdge(3 4 9);  g.AddEdge(3 5 14);  g.AddEdge(4 5 10);  g.AddEdge(5 6 2);  g.AddEdge(6 7 1);  g.AddEdge(6 8 6);  g.AddEdge(7 8 7);  g.ReverseDeleteMST();  } } // This code is contributed by Prithi_Dey 
Python3
# Python3 program to find Minimum Spanning Tree # of a graph using Reverse Delete Algorithm # Graph class represents a directed graph # using adjacency list representation class Graph: def __init__(self v): # No. of vertices self.v = v self.adj = [0] * v self.edges = [] for i in range(v): self.adj[i] = [] # function to add an edge to graph def addEdge(self u: int v: int w: int): self.adj[u].append(v) # Add w to v’s list. self.adj[v].append(u) # Add w to v’s list. self.edges.append((w (u v))) def dfs(self v: int visited: list): # Mark the current node as visited and print it visited[v] = True # Recur for all the vertices adjacent to # this vertex for i in self.adj[v]: if not visited[i]: self.dfs(i visited) # Returns true if graph is connected # Returns true if given graph is connected else false def connected(self): visited = [False] * self.v # Find all reachable vertices from first vertex self.dfs(0 visited) # If set of reachable vertices includes all # return true. for i in range(1 self.v): if not visited[i]: return False return True # This function assumes that edge (u v) # exists in graph or not def reverseDeleteMST(self): # Sort edges in increasing order on basis of cost self.edges.sort(key = lambda a: a[0]) mst_wt = 0 # Initialize weight of MST print('Edges in MST') # Iterate through all sorted edges in # decreasing order of weights for i in range(len(self.edges) - 1 -1 -1): u = self.edges[i][1][0] v = self.edges[i][1][1] # Remove edge from undirected graph self.adj[u].remove(v) self.adj[v].remove(u) # Adding the edge back if removing it # causes disconnection. In this case this # edge becomes part of MST. if self.connected() == False: self.adj[u].append(v) self.adj[v].append(u) # This edge is part of MST print('( %d %d )' % (u v)) mst_wt += self.edges[i][0] print('Total weight of MST is' mst_wt) # Driver Code if __name__ == '__main__': # create the graph given in above figure V = 9 g = Graph(V) # making above shown graph g.addEdge(0 1 4) g.addEdge(0 7 8) g.addEdge(1 2 8) g.addEdge(1 7 11) g.addEdge(2 3 7) g.addEdge(2 8 2) g.addEdge(2 5 4) g.addEdge(3 4 9) g.addEdge(3 5 14) g.addEdge(4 5 10) g.addEdge(5 6 2) g.addEdge(6 7 1) g.addEdge(6 8 6) g.addEdge(7 8 7) g.reverseDeleteMST() # This code is contributed by # sanjeev2552 
C#
// C# program to find Minimum Spanning Tree // of a graph using Reverse Delete Algorithm using System; using System.Collections.Generic; // class to represent an edge public class Edge : IComparable<Edge> {  public int u v w;  public Edge(int u int v int w)  {  this.u = u;  this.v = v;  this.w = w;  }  public int CompareTo(Edge other)  {  return this.w.CompareTo(other.w);  } } // Graph class represents a directed graph // using adjacency list representation public class Graph {  private int V; // No. of vertices  private List<int>[] adj;  private List<Edge> edges;  public Graph(int v) // Constructor  {  V = v;  adj = new List<int>[ v ];  for (int i = 0; i < v; i++)  adj[i] = new List<int>();  edges = new List<Edge>();  }  // function to Add an edge  public void AddEdge(int u int v int w)  {  adj[u].Add(v); // Add w to v’s list.  adj[v].Add(u); // Add w to v’s list.  edges.Add(new Edge(u v w));  }  // function to perform dfs  private void DFS(int v bool[] visited)  {  // Mark the current node as visited and print it  visited[v] = true;  // Recur for all the vertices adjacent to  // this vertex  foreach(int i in adj[v])  {  if (!visited[i])  DFS(i visited);  }  }  // Returns true if given graph is connected else false  private bool IsConnected()  {  bool[] visited = new bool[V];  // Find all reachable vertices from first vertex  DFS(0 visited);  // If set of reachable vertices includes all  // return true.  for (int i = 1; i < V; i++) {  if (visited[i] == false)  return false;  }  return true;  }  // This function assumes that edge (u v)  // exists in graph or not  public void ReverseDeleteMST()  {  // Sort edges in increasing order on basis of cost  edges.Sort();  int mst_wt = 0; // Initialize weight of MST  Console.WriteLine('Edges in MST');  // Iterate through all sorted edges in  // decreasing order of weights  for (int i = edges.Count - 1; i >= 0; i--) {  int u = edges[i].u;  int v = edges[i].v;  // Remove edge from undirected graph  adj[u].Remove(v);  adj[v].Remove(u);  // Adding the edge back if removing it  // causes disconnection. In this case this  // edge becomes part of MST.  if (IsConnected() == false) {  adj[u].Add(v);  adj[v].Add(u);  // This edge is part of MST  Console.WriteLine('({0} {1})' u v);  mst_wt += edges[i].w;  }  }  Console.WriteLine('Total weight of MST is {0}'  mst_wt);  } } class GFG {  // Driver code  static void Main(string[] args)  {  // create the graph given in above figure  int V = 9;  Graph g = new Graph(V);  // making above shown graph  g.AddEdge(0 1 4);  g.AddEdge(0 7 8);  g.AddEdge(1 2 8);  g.AddEdge(1 7 11);  g.AddEdge(2 3 7);  g.AddEdge(2 8 2);  g.AddEdge(2 5 4);  g.AddEdge(3 4 9);  g.AddEdge(3 5 14);  g.AddEdge(4 5 10);  g.AddEdge(5 6 2);  g.AddEdge(6 7 1);  g.AddEdge(6 8 6);  g.AddEdge(7 8 7);  g.ReverseDeleteMST();  } } // This code is contributed by cavi4762 
JavaScript
// Javascript program to find Minimum Spanning Tree // of a graph using Reverse Delete Algorithm // Graph class represents a directed graph // using adjacency list representation class Graph {  // Constructor  constructor(V) {  this.V = V;  this.adj = [];  this.edges = [];  for (let i = 0; i < V; i++) {  this.adj[i] = [];  }  }    // function to add an edge to graph  addEdge(u v w) {  this.adj[u].push(v);// Add w to v’s list.  this.adj[v].push(u);// Add w to v’s list.  this.edges.push([w [u v]]);  }  DFS(v visited) {  // Mark the current node as visited and print it  visited[v] = true;  for (const i of this.adj[v]) {  if (!visited[i]) {  this.DFS(i visited);  }  }  }  // Returns true if given graph is connected else false  isConnected() {  const visited = [];  for (let i = 0; i < this.V; i++) {  visited[i] = false;  }    // Find all reachable vertices from first vertex  this.DFS(0 visited);    // If set of reachable vertices includes all  // return true.  for (let i = 1; i < this.V; i++) {  if (!visited[i]) {  return false;  }  }  return true;  }  // This function assumes that edge (u v)  // exists in graph or not  reverseDeleteMST() {    // Sort edges in increasing order on basis of cost  this.edges.sort((a b) => a[0] - b[0]);    let mstWt = 0;// Initialize weight of MST    console.log('Edges in MST');    // Iterate through all sorted edges in  // decreasing order of weights  for (let i = this.edges.length - 1; i >= 0; i--) {  const [u v] = this.edges[i][1];    // Remove edge from undirected graph  this.adj[u] = this.adj[u].filter(x => x !== v);  this.adj[v] = this.adj[v].filter(x => x !== u);    // Adding the edge back if removing it  // causes disconnection. In this case this   // edge becomes part of MST.  if (!this.isConnected()) {  this.adj[u].push(v);  this.adj[v].push(u);    // This edge is part of MST  console.log(`(${u} ${v})`);  mstWt += this.edges[i][0];  }  }  console.log(`Total weight of MST is ${mstWt}`);  } } // Driver code function main() {  // create the graph given in above figure  var V = 9;  var g = new Graph(V);  // making above shown graph  g.addEdge(0 1 4);  g.addEdge(0 7 8);  g.addEdge(1 2 8);  g.addEdge(1 7 11);  g.addEdge(2 3 7);  g.addEdge(2 8 2);  g.addEdge(2 5 4);  g.addEdge(3 4 9);  g.addEdge(3 5 14);  g.addEdge(4 5 10);  g.addEdge(5 6 2);  g.addEdge(6 7 1);  g.addEdge(6 8 6);  g.addEdge(7 8 7);  g.reverseDeleteMST(); } main(); 

Produktion
Edges in MST (3 4) (0 7) (2 3) (2 5) (0 1) (5 6) (2 8) (6 7) Total weight of MST is 37 

Tidskomplexitet: O((E*(V+E)) + E log E) där E är antalet kanter.

Rymdkomplexitet: O(V+E) där V är antalet hörn och E är antalet kanter. Vi använder närliggande lista för att lagra grafen så vi behöver utrymme proportionellt mot O(V+E).

Anmärkningar: 

faktoriell java
  1. Ovanstående implementering är en enkel/naiv implementering av Reverse Delete-algoritmen och kan optimeras till O(E log V (log log V)3) [Källa: En vecka ]. Men denna optimerade tidskomplexitet är fortfarande mindre än Prim och Kruskal Algoritmer för MST.
  2. Implementeringen ovan ändrar den ursprungliga grafen. Vi kan skapa en kopia av grafen om originalgrafen måste behållas.

 

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