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AntColonyOptimization.java public class AntColonyOptimization { private double c = 1.0; private double alpha = 1; private double beta = 5; private double evaporation = 0.5;

AntColonyOptimization.java
public class AntColonyOptimization {
private double c = 1.0;
private double alpha = 1;
private double beta = 5;
private double evaporation = 0.5;
private double Q = 500;
private double antFactor = 0.8;
private double randomFactor = 0.01;
private int maxIterations = 1000;
private int numberOfCities;
private int numberOfAnts;
private double graph[][];
private double trails[][];
private List ants = new ArrayList<>();
private Random random = new Random();
private double probabilities[];
private int currentIndex;
private int[] bestTourOrder;
private double bestTourLength;
public AntColonyOptimization(int noOfCities) {
graph = generateRandomMatrix(noOfCities);
numberOfCities = graph.length;
numberOfAnts = (int) (numberOfCities * antFactor);
trails = new double[numberOfCities][numberOfCities];
probabilities = new double[numberOfCities];
IntStream.range(0, numberOfAnts).forEach(i -> ants.add(new Ant(numberOfCities)));
}
/**
* Generate initial solution
*/
public double[][] generateRandomMatrix(int n) {
double[][] randomMatrix = new double[n][n];
IntStream.range(0, n).forEach(
i -> IntStream.range(0, n).forEach(j -> randomMatrix[i][j] = Math.abs(random.nextInt(100) + 1)));
return randomMatrix;
}
/**
* Perform ant optimization
*/
public void startAntOptimization() {
IntStream.rangeClosed(1, 3).forEach(i -> {
System.out.println("Attempt #" + i);
solve();
});
}
/**
* Use this method to run the main logic
*/
public int[] solve() {
setupAnts();
clearTrails();
IntStream.range(0, maxIterations).forEach(i -> {
moveAnts();
updateTrails();
updateBest();
});
System.out.println("Best tour length: " + (bestTourLength - numberOfCities));
System.out.println("Best tour order: " + Arrays.toString(bestTourOrder));
return bestTourOrder.clone();
}
/**
* Prepare ants for the simulation
*/
private void setupAnts() {
IntStream.range(0, numberOfAnts).forEach(i -> {
ants.forEach(ant -> {
ant.clear();
ant.visitCity(-1, random.nextInt(numberOfCities));
});
});
currentIndex = 0;
}
/**
* At each iteration, move ants
*/
private void moveAnts() {
IntStream.range(currentIndex, numberOfCities - 1).forEach(i -> {
ants.forEach(ant -> ant.visitCity(currentIndex, selectNextCity(ant)));
currentIndex++;
});
}
/**
* Select next city for each ant
*/
private int selectNextCity(Ant ant) {
int t = random.nextInt(numberOfCities - currentIndex);
if (random.nextDouble() < randomFactor) {
OptionalInt cityIndex = IntStream.range(0, numberOfCities).filter(i -> i == t && !ant.visited(i))
.findFirst();
if (cityIndex.isPresent()) {
return cityIndex.getAsInt();
}
}
calculateProbabilities(ant);
double r = random.nextDouble();
double total = 0;
for (int i = 0; i < numberOfCities; i++) {
total += probabilities[i];
if (total >= r) {
return i;
}
}
throw new RuntimeException("There are no other cities");
}
/**
* Calculate the next city picks probabilites
*/
public void calculateProbabilities(Ant ant) {
int i = ant.trail[currentIndex];
double pheromone = 0.0;
for (int l = 0; l < numberOfCities; l++) {
if (!ant.visited(l)) {
pheromone += Math.pow(trails[i][l], alpha) * Math.pow(1.0 / graph[i][l], beta);
}
}
for (int j = 0; j < numberOfCities; j++) {
if (ant.visited(j)) {
probabilities[j] = 0.0;
} else {
double numerator = Math.pow(trails[i][j], alpha) * Math.pow(1.0 / graph[i][j], beta);
probabilities[j] = numerator / pheromone;
}
}
}
/**
* Update trails that ants used
*/
private void updateTrails() {
for (int i = 0; i < numberOfCities; i++) {
for (int j = 0; j < numberOfCities; j++) {
trails[i][j] *= evaporation;
}
}
for (Ant a : ants) {
double contribution = Q / a.trailLength(graph);
for (int i = 0; i < numberOfCities - 1; i++) {
trails[a.trail[i]][a.trail[i + 1]] += contribution;
}
trails[a.trail[numberOfCities - 1]][a.trail[0]] += contribution;
}
}
/**
* Update the best solution
*/
private void updateBest() {
if (bestTourOrder == null) {
bestTourOrder = ants.get(0).trail;
bestTourLength = ants.get(0).trailLength(graph);
}
for (Ant a : ants) {
if (a.trailLength(graph) < bestTourLength) {
bestTourLength = a.trailLength(graph);
bestTourOrder = a.trail.clone();
}
}
}
/**
* Clear trails after simulation
*/
private void clearTrails() {
IntStream.range(0, numberOfCities).forEach(i -> {
IntStream.range(0, numberOfCities).forEach(j -> trails[i][j] = c);
});
}
}
I NEED VHDL FOR THIS CODE

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