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Extract object creation

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This commit is contained in:
Laurent
2026-10-15 09:45:16 +02:00
parent a0f432b476
commit 18c6962744
5 changed files with 92 additions and 35 deletions
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21
src/main/java/Main.java
View File

@@ -1,10 +1,13 @@
import domain.annealing.SimulatedAnnealing;
import domain.ant_colony.AntColonyOptimization;
import domain.binary.Population;
import domain.binary.algorithm.AbstractGeneticAlgorithm;
import domain.binary.algorithm.AlgorithmEngine;
import domain.binary.algorithm.CustomGeneticAlgorithm;
import domain.binary.algorithm.SimpleGeneticAlgorithm;
import domain.binary.factory.GeneticAlgorithmFactory;
import javax.swing.*;
import java.util.Scanner;
public class Main {
@@ -21,15 +24,27 @@ public class Main {
System.out.println("Optimized distance for travel: " + SimulatedAnnealing.simulateAnnealing(10, 10000, 0.9995));
break;
case 2:
AbstractGeneticAlgorithm ga = new SimpleGeneticAlgorithm(
15,
AbstractGeneticAlgorithm simple = GeneticAlgorithmFactory.createSimple(
50,
0.5,
0.025,
5,
true,
"1011000100000100010000100000100111001000000100000100000000001111"
);
AlgorithmEngine.start(ga);
AbstractGeneticAlgorithm custom = GeneticAlgorithmFactory.createCustom(
50,
0.5,
0.025,
5,
25,
true,
"1011000100000100010000100000100111001000000100000100000000001111"
);
AlgorithmEngine.start(simple);
break;
case 3:
AntColonyOptimization antColony = new AntColonyOptimization(21);

17
src/main/java/domain/binary/algorithm/AbstractGeneticAlgorithm.java
View File

@@ -8,9 +8,9 @@ public abstract class AbstractGeneticAlgorithm {
private byte[] solution;
private int generationCount;
public AbstractGeneticAlgorithm(String solution) {
public AbstractGeneticAlgorithm(byte[] solution) {
generationCount = 0;
this.solution = mapSolution(solution);
this.solution = solution;
}
public void incrementGenerationCount(){
@@ -23,17 +23,4 @@ public abstract class AbstractGeneticAlgorithm {
protected int getMaxFitness() {
return solution.length;
}
private byte[] mapSolution(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;
}
}
return solution;
}
}

11
src/main/java/domain/binary/algorithm/CustomGeneticAlgorithm.java
View File

@@ -1,19 +1,18 @@
package domain.binary.algorithm;
import domain.binary.Population;
public class CustomGeneticAlgorithm extends SimpleGeneticAlgorithm {
private final int maxGenerationCount;
public CustomGeneticAlgorithm(
int popSize,
Population population,
int maxGenerationCount,
double uniformRate,
double mutationRate,
int tournamentSize,
boolean elitism,
String solution
byte[] solution
) {
super(popSize, uniformRate, mutationRate, tournamentSize, elitism, solution);
super(population, elitism, solution);
this.maxGenerationCount = maxGenerationCount;
}

14
src/main/java/domain/binary/algorithm/SimpleGeneticAlgorithm.java
View File

@@ -9,20 +9,12 @@ public class SimpleGeneticAlgorithm extends AbstractGeneticAlgorithm{
private final boolean elitism;
public SimpleGeneticAlgorithm(
int popSize,
double uniformRate,
double mutationRate,
int tournamentSize,
Population population,
boolean elitism,
String solution
byte[] solution
){
super(solution);
this.population = new Population(
popSize,
uniformRate,
mutationRate,
tournamentSize,
getSolution());
this.population = population;
this.elitism = elitism;
}

64
src/main/java/domain/binary/factory/GeneticAlgorithmFactory.java Normal file
View File

@@ -0,0 +1,64 @@
package domain.binary.factory;
import domain.binary.Population;
import domain.binary.algorithm.CustomGeneticAlgorithm;
import domain.binary.algorithm.SimpleGeneticAlgorithm;
public class GeneticAlgorithmFactory {
public static SimpleGeneticAlgorithm createSimple(
int popSize,
double uniformRate,
double mutationRate,
int tournamentSize,
boolean elitism,
String solution
){
byte[] mappedSolution = mapSolution(solution);
Population population = createPopulation(popSize, uniformRate, mutationRate, tournamentSize, mappedSolution);
return new SimpleGeneticAlgorithm(population, elitism, mappedSolution);
}
public static CustomGeneticAlgorithm createCustom(
int popSize,
double uniformRate,
double mutationRate,
int tournamentSize,
int maxGenerationCount,
boolean elitism,
String solution
){
byte[] mappedSolution = mapSolution(solution);
Population population = createPopulation(popSize, uniformRate, mutationRate, tournamentSize, mappedSolution);
return new CustomGeneticAlgorithm(population, maxGenerationCount, elitism, mappedSolution);
}
private static Population createPopulation(
int popSize,
double uniformRate,
double mutationRate,
int tournamentSize,
byte[] solution
){
return new Population(
popSize,
uniformRate,
mutationRate,
tournamentSize,
solution);
}
private static byte[] mapSolution(String newSolution) {
byte[] 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;
}
}
return solution;
}
}