Dijkstra算法在Java中的实现
这是Djikstra算法在java中的实现,我从《算法导论》一书开始就遵循了这一点。但在某些情况下,结果并不准确。对于下图,输出显示顶点F与源顶点A的最小距离为16,实际上是12。我对算法还比较陌生,所以欢迎对代码的改进提出任何建议。 enter image description here 图表
程序代码为:
Graph.Java
package Djikstra;
import java.io.File;
import java.io.FileNotFoundException;
import java.util.Scanner;
import Djikstra.Vertex;
public class Graph {
Vertex[] vertexes;
public Graph(String file) throws FileNotFoundException{
Scanner sc = new Scanner(new File(file));
vertexes=new Vertex[sc.nextInt()];
for (int v = 0; v < vertexes.length; v++){
vertexes[v] = new Vertex(sc.next());
}
while (sc.hasNext()) {
int v1= indexForName(sc.next()); //read source vertex
String destination=sc.next(); //read destination vertex
int w=sc.nextInt(); //read weight of the edge
vertexes[v1].neighbours.put(destination, w); //put the edge adjacent to source vertex
}
sc.close();
}
public int indexForName(String name) {
for (int v = 0; v < vertexes.length; v++) {
if (vertexes[v].id.equals(name))
return v;
}
return -1;
}
}
Dijkstra.java
package Djikstra;
import Djikstra.Graph;
import java.io.FileNotFoundException;
import java.util.Comparator;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Map;
import java.util.PriorityQueue;
import java.util.Queue;
import java.util.Set;
public class Dijkstra {
Graph graph;;
public Dijkstra(String file) throws FileNotFoundException{
graph = new Graph(file);
}
public void initialiseSingleSource(Graph G,int s){ //set min distance of all vertex to infinite and parent to null
for(Vertex v:G.vertexes){
v.d=1000;
v.p=null;
}
G.vertexes[s].d=0; //set min distance of source to 0
}
public void relax(Vertex u,Vertex v,int weight){
if(v.d>(u.d + weight)){
v.d=u.d+weight;
v.p=u;
}
}
public int weightFunc(Graph G,Vertex u,Vertex v){ //to get weight of an edge from vertex u to v
int weight=u.neighbours.get(v.id);
return weight;
}
public class VertexComparator implements Comparator<Vertex>{ //min priority queue keyed by their d(min distance from source) values
@Override
public int compare(Vertex v1, Vertex v2) {
return (v1.d-v2.d);
}
}
public int indexForName(Graph G,String name) { //to get index from the id of vertex
for (int v = 0; v < G.vertexes.length; v++) {
if (G.vertexes[v].id.equals(name))
return v;
}
return -1;
}
public Set<Vertex> dijkstraAlgo(Graph G,int s){
initialiseSingleSource(G,s);
Set<Vertex> set=new HashSet<Vertex>(); //intitially empty set of vertexes
Queue<Vertex> Q=new PriorityQueue<Vertex>(10,new VertexComparator()); //min priority queue
for(Vertex v:G.vertexes) //add all vertexes to priority queue
Q.add(v);
while(Q.size()!=0){
Vertex u=Q.poll(); //extract vertex which have min distance in priority queue
set.add(u); //add that vertex to set
for(String vertexId:u.neighbours.keySet()){ //see neighbours of vertex extracted
int vertexNum=indexForName(G,vertexId); //get index for neighbour vertex in vertexes array
Vertex v=G.vertexes[vertexNum];
int w=weightFunc(G,u,v); //get weight of edge from Vertex u to v
relax(u,v,w);
}
}
return set;
}
public static void main(String[] args) throws FileNotFoundException{
String fileName = "C:/Users/Dell PC/Algorithm_Workspace/Graph_CLRS/src/Djikstra/dijkstraGraph.txt";
Dijkstra dijkstra=new Dijkstra(fileName);
Set<Vertex> vertexInfo=dijkstra.dijkstraAlgo(dijkstra.graph, 0);
System.out.println("Printing min distance of all vertexes from source vertex A ");
for(Vertex v:vertexInfo){
System.out.println("Id: " + v.id + " distance: " + v.d);
}
}
}
class Vertex{
String id;
int d; //to store min distance from source
Vertex p; //to store last vertex from which min distance is reached
Map<String,Integer> neighbours; //to store edges of adjacent to the vertex
public Vertex(String id){
this.id=id;
neighbours=new HashMap<String,Integer>();
}
}
The input file dijkstraGraph.txt
7
A
B
C
D
E
F
G
A B 5
A C 10
B E 3
B D 6
D F 6
E C 2
E G 2
E D 2
G F 2
Output:
Printing min distance of all vertexes from source vertex A
Id: A distance: 0
Id: G distance: 10
Id: F distance: 16
Id: E distance: 8
Id: C distance: 10
Id: D distance: 10
Id: B distance: 5
# 1 楼答案
与其用所有节点初始化队列
Q
,不如用源节点初始化它然后,当你迭代这些邻居时,将它们添加到
Q
新产出: