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Final fixes on ACO (#1339)

Browse Source 
* Ant Colony Optimization

* Updated code for Ant Colony
This commit is contained in:
maibin
2017-03-09 04:21:47 +01:00
committed by KevinGilmore
parent 18710230ab
commit 3abb98e9e8
23 changed files with 226 additions and 200 deletions
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7
algorithms/pom.xml
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@@ -9,6 +9,7 @@
<junit.version>4.12</junit.version>
<maven-compiler-plugin.version>3.6.0</maven-compiler-plugin.version>
<exec-maven-plugin.version>1.5.0</exec-maven-plugin.version>
<lombok.version>1.16.12</lombok.version>
</properties>
<dependencies>
@@ -18,6 +19,12 @@
<version>${junit.version}</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>${lombok.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>
<build>

47
algorithms/src/main/java/com/baeldung/algorithms/RunAlgorithm.java Normal file
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package com.baeldung.algorithms;
import java.util.Scanner;
import com.baeldung.algorithms.ga.annealing.SimulatedAnnealing;
import com.baeldung.algorithms.ga.ant_colony.AntColonyOptimization;
import com.baeldung.algorithms.ga.binary.SimpleGeneticAlgorithm;
import com.baeldung.algorithms.slope_one.SlopeOne;
public class RunAlgorithm {
public static void main(String[] args) throws InstantiationException, IllegalAccessException {
Scanner in = new Scanner(System.in);
System.out.println("Run algorithm:");
System.out.println("1 - Simulated Annealing");
System.out.println("2 - Slope One");
System.out.println("3 - Simple Genetic Algorithm");
System.out.println("4 - Ant Colony");
System.out.println("5 - Dijkstra");
int decision = in.nextInt();
switch (decision) {
case 1:
System.out.println(
"Optimized distance for travel: " + SimulatedAnnealing.simulateAnnealing(10, 10000, 0.9995));
break;
case 2:
SlopeOne.slopeOne(3);
break;
case 3:
SimpleGeneticAlgorithm ga = new SimpleGeneticAlgorithm();
ga.runAlgorithm(50, "1011000100000100010000100000100111001000000100000100000000001111");
break;
case 4:
AntColonyOptimization antColony = new AntColonyOptimization(21);
antColony.startAntOptimization();
break;
case 5:
System.out.println("Please run the DijkstraAlgorithmTest.");
break;
default:
System.out.println("Unknown option");
break;
}
in.close();
}
}

22
algorithms/src/main/java/com/baeldung/algorithms/ga/annealing/City.java Normal file
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package com.baeldung.algorithms.ga.annealing;
import lombok.Data;
@Data
public class City {
private int x;
private int y;
public City() {
this.x = (int) (Math.random() * 500);
this.y = (int) (Math.random() * 500);
}
public double distanceToCity(City city) {
int x = Math.abs(getX() - city.getX());
int y = Math.abs(getY() - city.getY());
return Math.sqrt(Math.pow(x, 2) + Math.pow(y, 2));
}
}

36
algorithms/src/main/java/com/baeldung/algorithms/ga/annealing/SimulatedAnnealing.java Normal file
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package com.baeldung.algorithms.ga.annealing;
public class SimulatedAnnealing {
private static Travel travel = new Travel(10);
public static double simulateAnnealing(double startingTemperature, int numberOfIterations, double coolingRate) {
System.out.println("Starting SA with temperature: " + startingTemperature + ", # of iterations: " + numberOfIterations + " and colling rate: " + coolingRate);
double t = startingTemperature;
travel.generateInitialTravel();
double bestDistance = travel.getDistance();
System.out.println("Initial distance of travel: " + bestDistance);
Travel bestSolution = travel;
Travel currentSolution = bestSolution;
for (int i = 0; i < numberOfIterations; i++) {
if (t > 0.1) {
currentSolution.swapCities();
double currentDistance = currentSolution.getDistance();
if (currentDistance < bestDistance) {
bestDistance = currentDistance;
} else if (Math.exp((bestDistance - currentDistance) / t) < Math.random()) {
currentSolution.revertSwap();
}
t *= coolingRate;
} else {
continue;
}
if (i % 100 == 0) {
System.out.println("Iteration #" + i);
}
}
return bestDistance;
}
}

63
algorithms/src/main/java/com/baeldung/algorithms/ga/annealing/Travel.java Normal file
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@@ -0,0 +1,63 @@
package com.baeldung.algorithms.ga.annealing;
import java.util.ArrayList;
import java.util.Collections;
import lombok.Data;
@Data
public class Travel {
private ArrayList<City> travel = new ArrayList<>();
private ArrayList<City> previousTravel = new ArrayList<>();
public Travel(int numberOfCities) {
for (int i = 0; i < numberOfCities; i++) {
travel.add(new City());
}
}
public void generateInitialTravel() {
if (travel.isEmpty())
new Travel(10);
Collections.shuffle(travel);
}
public void swapCities() {
int a = generateRandomIndex();
int b = generateRandomIndex();
previousTravel = travel;
City x = travel.get(a);
City y = travel.get(b);
travel.set(a, y);
travel.set(b, x);
}
public void revertSwap() {
travel = previousTravel;
}
private int generateRandomIndex() {
return (int) (Math.random() * travel.size());
}
public City getCity(int index) {
return travel.get(index);
}
public int getDistance() {
int distance = 0;
for (int index = 0; index < travel.size(); index++) {
City starting = getCity(index);
City destination;
if (index + 1 < travel.size()) {
destination = getCity(index + 1);
} else {
destination = getCity(0);
}
distance += starting.distanceToCity(destination);
}
return distance;
}
}

37
algorithms/src/main/java/com/baeldung/algorithms/ga/ant_colony/Ant.java Normal file
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package com.baeldung.algorithms.ga.ant_colony;
public class Ant {
protected int trailSize;
protected int trail[];
protected boolean visited[];
public Ant(int tourSize) {
this.trailSize = tourSize;
this.trail = new int[tourSize];
this.visited = new boolean[tourSize];
}
protected void visitCity(int currentIndex, int city) {
trail[currentIndex + 1] = city;
visited[city] = true;
}
protected boolean visited(int i) {
return visited[i];
}
protected double trailLength(double graph[][]) {
double length = graph[trail[trailSize - 1]][trail[0]];
for (int i = 0; i < trailSize - 1; i++) {
length += graph[trail[i]][trail[i + 1]];
}
return length;
}
protected void clear() {
for (int i = 0; i < trailSize; i++)
visited[i] = false;
}
}

203
algorithms/src/main/java/com/baeldung/algorithms/ga/ant_colony/AntColonyOptimization.java Normal file
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package com.baeldung.algorithms.ga.ant_colony;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.OptionalInt;
import java.util.Random;
import java.util.stream.IntStream;
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<Ant> 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);
});
}
}

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algorithms/src/main/java/com/baeldung/algorithms/ga/binary/Individual.java Normal file
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package com.baeldung.algorithms.ga.binary;
import lombok.Data;
@Data
public class Individual {
protected int defaultGeneLength = 64;
private byte[] genes = new byte[defaultGeneLength];
private int fitness = 0;
public Individual() {
for (int i = 0; i < genes.length; i++) {
byte gene = (byte) Math.round(Math.random());
genes[i] = gene;
}
}
protected byte getSingleGene(int index) {
return genes[index];
}
protected void setSingleGene(int index, byte value) {
genes[index] = value;
fitness = 0;
}
public int getFitness() {
if (fitness == 0) {
fitness = SimpleGeneticAlgorithm.getFitness(this);
}
return fitness;
}
@Override
public String toString() {
String geneString = "";
for (int i = 0; i < genes.length; i++) {
geneString += getSingleGene(i);
}
return geneString;
}
}

40
algorithms/src/main/java/com/baeldung/algorithms/ga/binary/Population.java Normal file
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package com.baeldung.algorithms.ga.binary;
import java.util.ArrayList;
import java.util.List;
import lombok.Data;
@Data
public class Population {
private List<Individual> individuals;
public Population(int size, boolean createNew) {
individuals = new ArrayList<>();
if (createNew) {
createNewPopulation(size);
}
}
protected Individual getIndividual(int index) {
return individuals.get(index);
}
protected Individual getFittest() {
Individual fittest = individuals.get(0);
for (int i = 0; i < individuals.size(); i++) {
if (fittest.getFitness() <= getIndividual(i).getFitness()) {
fittest = getIndividual(i);
}
}
return fittest;
}
private void createNewPopulation(int size) {
for (int i = 0; i < size; i++) {
Individual newIndividual = new Individual();
individuals.add(i, newIndividual);
}
}
}

117
algorithms/src/main/java/com/baeldung/algorithms/ga/binary/SimpleGeneticAlgorithm.java Normal file
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package com.baeldung.algorithms.ga.binary;
import lombok.Data;
@Data
public class SimpleGeneticAlgorithm {
private static final double uniformRate = 0.5;
private static final double mutationRate = 0.025;
private static final int tournamentSize = 5;
private static final boolean elitism = true;
private static byte[] solution = new byte[64];
public boolean runAlgorithm(int populationSize, String solution) {
if (solution.length() != SimpleGeneticAlgorithm.solution.length) {
throw new RuntimeException("The solution needs to have " + SimpleGeneticAlgorithm.solution.length + " bytes");
}
setSolution(solution);
Population myPop = new Population(populationSize, true);
int generationCount = 1;
while (myPop.getFittest().getFitness() < getMaxFitness()) {
System.out.println("Generation: " + generationCount + " Correct genes found: " + myPop.getFittest().getFitness());
myPop = evolvePopulation(myPop);
generationCount++;
}
System.out.println("Solution found!");
System.out.println("Generation: " + generationCount);
System.out.println("Genes: ");
System.out.println(myPop.getFittest());
return true;
}
public Population evolvePopulation(Population pop) {
int elitismOffset;
Population newPopulation = new Population(pop.getIndividuals().size(), false);
if (elitism) {
newPopulation.getIndividuals().add(0, pop.getFittest());
elitismOffset = 1;
} else {
elitismOffset = 0;
}
for (int i = elitismOffset; i < pop.getIndividuals().size(); i++) {
Individual indiv1 = tournamentSelection(pop);
Individual indiv2 = tournamentSelection(pop);
Individual newIndiv = crossover(indiv1, indiv2);
newPopulation.getIndividuals().add(i, newIndiv);
}
for (int i = elitismOffset; i < newPopulation.getIndividuals().size(); i++) {
mutate(newPopulation.getIndividual(i));
}
return newPopulation;
}
private Individual crossover(Individual indiv1, Individual indiv2) {
Individual newSol = new Individual();
for (int i = 0; i < newSol.getDefaultGeneLength(); i++) {
if (Math.random() <= uniformRate) {
newSol.setSingleGene(i, indiv1.getSingleGene(i));
} else {
newSol.setSingleGene(i, indiv2.getSingleGene(i));
}
}
return newSol;
}
private void mutate(Individual indiv) {
for (int i = 0; i < indiv.getDefaultGeneLength(); i++) {
if (Math.random() <= mutationRate) {
byte gene = (byte) Math.round(Math.random());
indiv.setSingleGene(i, gene);
}
}
}
private Individual tournamentSelection(Population pop) {
Population tournament = new Population(tournamentSize, false);
for (int i = 0; i < tournamentSize; i++) {
int randomId = (int) (Math.random() * pop.getIndividuals().size());
tournament.getIndividuals().add(i, pop.getIndividual(randomId));
}
Individual fittest = tournament.getFittest();
return fittest;
}
protected static int getFitness(Individual individual) {
int fitness = 0;
for (int i = 0; i < individual.getDefaultGeneLength() && i < solution.length; i++) {
if (individual.getSingleGene(i) == solution[i]) {
fitness++;
}
}
return fitness;
}
protected int getMaxFitness() {
int maxFitness = solution.length;
return maxFitness;
}
protected void setSolution(String newSolution) {
solution = new byte[newSolution.length()];
for (int i = 0; i < newSolution.length(); i++) {
String character = newSolution.substring(i, i + 1);
if (character.contains("0") || character.contains("1")) {
solution[i] = Byte.parseByte(character);
} else {
solution[i] = 0;
}
}
}
}

2
algorithms/src/main/java/com/baeldung/algorithms/dijkstra/Dijkstra.java → algorithms/src/main/java/com/baeldung/algorithms/ga/dijkstra/Dijkstra.java
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@@ -1,4 +1,4 @@
package com.baeldung.algorithms.dijkstra;
package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashSet;
import java.util.LinkedList;

2
algorithms/src/main/java/com/baeldung/algorithms/dijkstra/Graph.java → algorithms/src/main/java/com/baeldung/algorithms/ga/dijkstra/Graph.java
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@@ -1,4 +1,4 @@
package com.baeldung.algorithms.dijkstra;
package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashSet;
import java.util.Set;

2
algorithms/src/main/java/com/baeldung/algorithms/dijkstra/Node.java → algorithms/src/main/java/com/baeldung/algorithms/ga/dijkstra/Node.java
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@@ -1,4 +1,4 @@
package com.baeldung.algorithms.dijkstra;
package com.baeldung.algorithms.ga.dijkstra;
import java.util.HashMap;
import java.util.LinkedList;

35
algorithms/src/main/java/com/baeldung/algorithms/slope_one/InputData.java Normal file
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package com.baeldung.algorithms.slope_one;
import java.util.Arrays;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import lombok.Data;
@Data
public class InputData {
protected static List<Item> items = Arrays.asList(new Item("Candy"), new Item("Drink"), new Item("Soda"), new Item("Popcorn"), new Item("Snacks"));
public static Map<User, HashMap<Item, Double>> initializeData(int numberOfUsers) {
Map<User, HashMap<Item, Double>> data = new HashMap<>();
HashMap<Item, Double> newUser;
Set<Item> newRecommendationSet;
for (int i = 0; i < numberOfUsers; i++) {
newUser = new HashMap<Item, Double>();
newRecommendationSet = new HashSet<>();
for (int j = 0; j < 3; j++) {
newRecommendationSet.add(items.get((int) (Math.random() * 5)));
}
for (Item item : newRecommendationSet) {
newUser.put(item, Math.random());
}
data.put(new User("User " + i), newUser);
}
return data;
}
}

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algorithms/src/main/java/com/baeldung/algorithms/slope_one/Item.java Normal file
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package com.baeldung.algorithms.slope_one;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@NoArgsConstructor
@AllArgsConstructor
public class Item {
private String itemName;
}

124
algorithms/src/main/java/com/baeldung/algorithms/slope_one/SlopeOne.java Normal file
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package com.baeldung.algorithms.slope_one;
import java.text.DecimalFormat;
import java.text.NumberFormat;
import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;
/**
* Slope One algorithm implementation
*/
public class SlopeOne {
private static Map<Item, Map<Item, Double>> diff = new HashMap<>();
private static Map<Item, Map<Item, Integer>> freq = new HashMap<>();
private static Map<User, HashMap<Item, Double>> inputData;
private static Map<User, HashMap<Item, Double>> outputData = new HashMap<>();
public static void slopeOne(int numberOfUsers) {
inputData = InputData.initializeData(numberOfUsers);
System.out.println("Slope One - Before the Prediction\n");
buildDifferencesMatrix(inputData);
System.out.println("\nSlope One - With Predictions\n");
predict(inputData);
}
/**
* Based on the available data, calculate the relationships between the
* items and number of occurences
*
* @param data
* existing user data and their items' ratings
*/
private static void buildDifferencesMatrix(Map<User, HashMap<Item, Double>> data) {
for (HashMap<Item, Double> user : data.values()) {
for (Entry<Item, Double> e : user.entrySet()) {
if (!diff.containsKey(e.getKey())) {
diff.put(e.getKey(), new HashMap<Item, Double>());
freq.put(e.getKey(), new HashMap<Item, Integer>());
}
for (Entry<Item, Double> e2 : user.entrySet()) {
int oldCount = 0;
if (freq.get(e.getKey()).containsKey(e2.getKey())) {
oldCount = freq.get(e.getKey()).get(e2.getKey()).intValue();
}
double oldDiff = 0.0;
if (diff.get(e.getKey()).containsKey(e2.getKey())) {
oldDiff = diff.get(e.getKey()).get(e2.getKey()).doubleValue();
}
double observedDiff = e.getValue() - e2.getValue();
freq.get(e.getKey()).put(e2.getKey(), oldCount + 1);
diff.get(e.getKey()).put(e2.getKey(), oldDiff + observedDiff);
}
}
}
for (Item j : diff.keySet()) {
for (Item i : diff.get(j).keySet()) {
double oldValue = diff.get(j).get(i).doubleValue();
int count = freq.get(j).get(i).intValue();
diff.get(j).put(i, oldValue / count);
}
}
printData(data);
}
/**
* Based on existing data predict all missing ratings. If prediction is not
* possible, the value will be equal to -1
*
* @param data
* existing user data and their items' ratings
*/
private static void predict(Map<User, HashMap<Item, Double>> data) {
HashMap<Item, Double> uPred = new HashMap<Item, Double>();
HashMap<Item, Integer> uFreq = new HashMap<Item, Integer>();
for (Item j : diff.keySet()) {
uFreq.put(j, 0);
uPred.put(j, 0.0);
}
for (Entry<User, HashMap<Item, Double>> e : data.entrySet()) {
for (Item j : e.getValue().keySet()) {
for (Item k : diff.keySet()) {
try {
double predictedValue = diff.get(k).get(j).doubleValue() + e.getValue().get(j).doubleValue();
double finalValue = predictedValue * freq.get(k).get(j).intValue();
uPred.put(k, uPred.get(k) + finalValue);
uFreq.put(k, uFreq.get(k) + freq.get(k).get(j).intValue());
} catch (NullPointerException e1) {
}
}
}
HashMap<Item, Double> clean = new HashMap<Item, Double>();
for (Item j : uPred.keySet()) {
if (uFreq.get(j) > 0) {
clean.put(j, uPred.get(j).doubleValue() / uFreq.get(j).intValue());
}
}
for (Item j : InputData.items) {
if (e.getValue().containsKey(j)) {
clean.put(j, e.getValue().get(j));
} else {
clean.put(j, -1.0);
}
}
outputData.put(e.getKey(), clean);
}
printData(outputData);
}
private static void printData(Map<User, HashMap<Item, Double>> data) {
for (User user : data.keySet()) {
System.out.println(user.getUsername() + ":");
print(data.get(user));
}
}
private static void print(HashMap<Item, Double> hashMap) {
NumberFormat formatter = new DecimalFormat("#0.000");
for (Item j : hashMap.keySet()) {
System.out.println(" " + j.getItemName() + " --> " + formatter.format(hashMap.get(j).doubleValue()));
}
}
}

14
algorithms/src/main/java/com/baeldung/algorithms/slope_one/User.java Normal file
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@@ -0,0 +1,14 @@
package com.baeldung.algorithms.slope_one;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@NoArgsConstructor
@AllArgsConstructor
public class User {
private String username;
}

22
algorithms/src/test/java/algorithms/AntColonyOptimizationTest.java Normal file
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package algorithms;
import org.junit.Assert;
import org.junit.Test;
import com.baeldung.algorithms.ga.ant_colony.AntColonyOptimization;
public class AntColonyOptimizationTest {
@Test
public void testGenerateRandomMatrix() {
AntColonyOptimization antTSP = new AntColonyOptimization(5);
Assert.assertNotNull(antTSP.generateRandomMatrix(5));
}
@Test
public void testStartAntOptimization() {
AntColonyOptimization antTSP = new AntColonyOptimization(5);
Assert.assertNotNull(antTSP.solve());
}
}

16
algorithms/src/test/java/algorithms/BinaryGeneticAlgorithmUnitTest.java Normal file
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package algorithms;
import org.junit.Assert;
import org.junit.Test;
import com.baeldung.algorithms.ga.binary.SimpleGeneticAlgorithm;
public class BinaryGeneticAlgorithmUnitTest {
@Test
public void testGA() {
SimpleGeneticAlgorithm ga = new SimpleGeneticAlgorithm();
Assert.assertTrue(ga.runAlgorithm(50, "1011000100000100010000100000100111001000000100000100000000001111"));
}
}

7
algorithms/src/test/java/algorithms/DijkstraAlgorithmTest.java
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@@ -1,10 +1,11 @@
package algorithms;
import com.baeldung.algorithms.dijkstra.Dijkstra;
import com.baeldung.algorithms.dijkstra.Graph;
import com.baeldung.algorithms.dijkstra.Node;
import org.junit.Test;
import com.baeldung.algorithms.ga.dijkstra.Dijkstra;
import com.baeldung.algorithms.ga.dijkstra.Graph;
import com.baeldung.algorithms.ga.dijkstra.Node;
import java.util.Arrays;
import java.util.List;

15
algorithms/src/test/java/algorithms/SimulatedAnnealingTest.java Normal file
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package algorithms;
import org.junit.Assert;
import org.junit.Test;
import com.baeldung.algorithms.ga.annealing.SimulatedAnnealing;
public class SimulatedAnnealingTest {
@Test
public void testSimulateAnnealing() {
Assert.assertTrue(SimulatedAnnealing.simulateAnnealing(10, 1000, 0.9) > 0);
}
}