A* Path Finder (Java) is inefficient using a 1024 multidimentional array

I have the below code for a A* pathfinder, however it is taking upwards of 10 minutes to find a solution using a simple 1024 x 1024 array.

I had to comment out //Collections.sort(this.openList); as it was throwing a comparison method violates its general contract! error when running.

Is the algorithm correct and any idea why the bottleneck? Some people using C++ are getting a response time of 40ms, not 10+ mins!

When using the maze array it does it in the blink of an eye, but thats using something like a 14x10 array, rather than 1024 from the collisionMap.

Is the method flawed in some way? Or using the wrong data structures?

import java.util.List;
import javax.imageio.ImageIO;
import java.awt.Canvas;
import java.awt.Color;
import java.awt.GraphicsConfiguration;
import java.awt.Paint;
import java.awt.image.BufferedImage;
import java.io.Console;
import java.io.File;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collection;
import java.util.Collections;
import java.util.Comparator;
class AStarTwo {
// Closed list, open list and calculatedPath lists
private final List<Node> openList;
private final List<Node> closedList;
private final List<Node> calcPath;
// Collision Map to store tha map in
private final int[][] collisionMap;
// Current node the  program is executing
private Node currentNode;
// Define the start and end coords
private final int xstart;
private final int ystart;
private int xEnd, yEnd;
// Node class 
static class Node implements Comparable {
public Node parent;
public int x, y;
public double g;
public double h;
Node(Node parent, int xpos, int ypos, double g, double h) {
this.parent = parent;
this.x = xpos;
this.y = ypos;
this.g = g;
this.h = h;
}
// Compare f value (g + h)
@Override
public int compareTo(Object o) {
Node that = (Node) o;
return (int)((this.g + this.h) - (that.g + that.h));
}
}
// construct and initialise 
public AStarTwo(int[][] collisionMap, int xstart, int ystart) {
this.openList = new ArrayList<>();
this.closedList = new ArrayList<>();
this.calcPath = new ArrayList<>();
this.collisionMap = collisionMap;
this.currentNode = new Node(null, xstart, ystart, 0, 0);
this.xstart = xstart;
this.ystart = ystart;
}
// returns a List<> of nodes to target
public List<Node> findPathTo(int xTo, int yTo) {
this.xEnd = xTo;
this.yEnd = yTo;
// Add this to the closed list
this.closedList.add(this.currentNode);
// Add neighbours to openList for iteration
addNeigborsToOpenList();
// Whilst not at our target
while (this.currentNode.x != this.xEnd || this.currentNode.y != this.yEnd) {
// If nothing in the open list then return with null - handled in error message in main calling func
if (this.openList.isEmpty()) {
return null;
}
// get the lowest f value and add it to the closed list, f calculated when neighbours are sorted
this.currentNode = this.openList.get(0);
this.openList.remove(0); 
this.closedList.add(this.currentNode); 
addNeigborsToOpenList();
}
// add this node to the calculated path
this.calcPath.add(0, this.currentNode);
while (this.currentNode.x != this.xstart || this.currentNode.y != this.ystart) {
this.currentNode = this.currentNode.parent;
this.calcPath.add(0, this.currentNode);
}
return this.calcPath;
}
// Searches the current list for neighbouring nodes returns bool
private static boolean checkNeighbourHasBeenSearched(List<Node> array, Node node) {
return array.stream().anyMatch((n) -> (n.x == node.x && n.y == node.y));
}
// Calculate distance from current node to the target
private double distance(int dx, int dy) {
return Math.hypot(this.currentNode.x + dx - this.xEnd, this.currentNode.y + dy - this.yEnd); // return hypothenuse
}
// Add neighbouring nodes to the open list to iterate through next
@SuppressWarnings("unchecked")
private void addNeigborsToOpenList() {
Node node;
for (int x = -1; x <= 1; x++) {
for (int y = -1; y <= 1; y++) {
node = new Node(this.currentNode, this.currentNode.x + x, this.currentNode.y + y, this.currentNode.g, this.distance(x, y));
// if we are not on the current node
if ((x != 0 || y != 0) 
&& this.currentNode.x + x >= 0 && this.currentNode.x + x < this.collisionMap[0].length // check collision map boundaries
&& this.currentNode.y + y >= 0 && this.currentNode.y + y < this.collisionMap.length
&& this.collisionMap[this.currentNode.y + y][this.currentNode.x + x] != -1) { // check if tile is walkable (-1)
// and finally check we haven't already searched the nodes
if(!checkNeighbourHasBeenSearched(this.openList, node) && !checkNeighbourHasBeenSearched(this.closedList, node)){
node.g = node.parent.g + 1.; // Horizontal/vertical cost = 1.0
node.g += collisionMap[this.currentNode.y + y][this.currentNode.x + x]; // add movement cost for this square
// Add diagonal movement cost sqrt(hor_cost² + vert_cost²) + 0.4
if (x != 0 && y != 0) {
node.g += .4;	
}
// Add the node to the List<>
this.openList.add(node);
}
}
}
}
// sort in ascending order
//Collections.sort(this.openList);
}
public static void main(String[] args) {
int [][] maze = 
{ {1,1,1,1,1,1,1,1,1,1,1,1,1},
{1,0,-1,0,-1,0,1,0,0,0,0,0,1},
{1,0,-1,0,0,0,1,0,1,1,1,0,1},
{1,0,0,0,-1,-1,-1,0,0,0,0,0,1},
{1,0,1,0,0,0,0,0,1,1,1,0,1},
{1,0,1,0,-1,-1,-1,0,1,0,0,0,-1},
{1,0,-1,0,-1,0,0,0,-1,-1,-1,0,-1},
{1,0,1,0,-1,-1,-1,0,1,0,-1,0,-1},
{1,0,0,0,0,0,0,0,0,0,1,0,1},
{1,1,1,1,1,1,1,1,1,1,1,1,1}
};
// Define the size of the grid
final int sizeOf = 20;
int[][] collisionMap = new int[sizeOf][];
for(int i=0;i < sizeOf; i++) {
// -1 = blocked
// 0+ = cost
collisionMap[i] = new int[sizeOf];
}
// set the value of the nodes
for (int k = 0; k < sizeOf; k++) {
for (int j = 0; j < sizeOf; j++) {
if(j == 30 && k < 100) {
collisionMap[k][j] = -1;
} else if (j == 50 && k > 230) {
collisionMap[k][j] = -1;
}else {
collisionMap[k][j] = 0;
}
}
}        
AStarTwo as = new AStarTwo(maze, 9, 9);
List<Node> path = as.findPathTo(0,0);
if(path == null) {
System.out.println("Unable to reach target");
}
// create image buffer to write output to
BufferedImage img = new BufferedImage(sizeOf, sizeOf, BufferedImage.TYPE_INT_RGB);
// Set colours
int r = 255;
int g = 0;
int b = 0; 
int colRed = (r << 16) | (g << 8) | b;
r = 0;
g = 255;
b = 0; 
int colGreen = (r << 16) | (g << 8) | b;
r = 0;
g = 0;
b = 255; 
int colBlue = (r << 16) | (g << 8) | b;
r = 255;
g = 255;
b = 255; 
int colWhite = (r << 16) | (g << 8) | b;
int i = 0;
int j = 0;
if (path != null) {
path.forEach((n) -> {
System.out.print("[" + n.x + ", " + n.y + "] ");
maze[n.y][n.x] = 2;
});
for (int[] maze_row : maze) {
for (int maze_entry : maze_row) {
switch (maze_entry) {
// normal tile
case 0:
img.setRGB(j, i, colWhite);
break;
// final path
case 2:
img.setRGB(j, i, colBlue);
break;
// Object to avoid
case -1:
img.setRGB(j, i, colRed);
break;
// Any other value
default:
img.setRGB(j, i, colWhite);
}
j++;
}
// count j - reset as if it were a for loop
if(i != 12) {
j=0;
}
i++;
System.out.println();
}
}
// output file
File f = new File("aStarPath.png");
try {
ImageIO.write(img, "PNG", f);
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
System.out.println("i: " + i + ", j: " + j);
}
}

I suspect your problem is this line:

return array.stream().anyMatch((n) -> (n.x == node.x && n.y == node.y));

which is called around O(n^2) times and will take time proportional to the size of the array (which will also be O(n^2) in the worst case for a n by n maze).

You want a faster method of performing this test.

For example:

1. Use a set to hold the open and closed lists instead of list
2. Or use an extra field in the node structure to indicate if it is in the open or closed list