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Laurent
2026-10-14 20:24:45 +02:00
parent 8469d66a87
commit 8c92c644a9
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.gradle
build/
!gradle/wrapper/gradle-wrapper.jar
!**/src/main/**/build/
!**/src/test/**/build/
.kotlin
### IntelliJ IDEA ###
.idea/modules.xml
.idea/jarRepositories.xml
.idea/compiler.xml
.idea/libraries/
*.iws
*.iml
*.ipr
out/
!**/src/main/**/out/
!**/src/test/**/out/
### Eclipse ###
.apt_generated
.classpath
.factorypath
.project
.settings
.springBeans
.sts4-cache
bin/
!**/src/main/**/bin/
!**/src/test/**/bin/
### NetBeans ###
/nbproject/private/
/nbbuild/
/dist/
/nbdist/
/.nb-gradle/
### VS Code ###
.vscode/
### Mac OS ###
.DS_Store

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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="GradleMigrationSettings" migrationVersion="1" />
<component name="GradleSettings">
<option name="linkedExternalProjectsSettings">
<GradleProjectSettings>
<option name="externalProjectPath" value="$PROJECT_DIR$" />
<option name="gradleHome" value="" />
<option name="modules">
<set>
<option value="$PROJECT_DIR$" />
</set>
</option>
</GradleProjectSettings>
</option>
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ExternalStorageConfigurationManager" enabled="true" />
<component name="FrameworkDetectionExcludesConfiguration">
<file type="web" url="file://$PROJECT_DIR$" />
</component>
<component name="ProjectRootManager" version="2" languageLevel="JDK_21" default="true" project-jdk-name="21" project-jdk-type="JavaSDK">
<output url="file://$PROJECT_DIR$/out" />
</component>
</project>

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assignement.md Normal file
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## Refactor
### Change dependency graph
- A circular dependency between SimpleGeneticAlgorithm and Individual were implemented using service locator pattern and
static classes.
### Population
- Add a second constructor. size parameter were never used if createNew was false
### Individual
- Move getFitness method from SimpleGeneticAlgorithm to Individual
### Prepare support for class inheritance
## Limit number of generations
## Roulette selection
To be done
## Cross-over rate
To be done
## Variable-length bit strings
To be done

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build.gradle.kts Normal file
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plugins {
id("java")
}
group = "be.naaturel"
version = "1.0-SNAPSHOT"
repositories {
mavenCentral()
}
dependencies {
implementation("io.jenetics:jenetics:5.1.0")
compileOnly("org.projectlombok:lombok:1.18.48")
annotationProcessor("org.projectlombok:lombok:1.18.48")
testCompileOnly("org.projectlombok:lombok:1.18.48")
testAnnotationProcessor("org.projectlombok:lombok:1.18.48")
testImplementation(platform("org.junit:junit-bom:5.10.0"))
testImplementation("org.junit.jupiter:junit-jupiter")
testRuntimeOnly("org.junit.platform:junit-platform-launcher")
}
tasks.test {
useJUnitPlatform()
}

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gradle/wrapper/gradle-wrapper.properties vendored Normal file
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#Wed Sep 23 14:50:08 CEST 2026
distributionBase=GRADLE_USER_HOME
distributionPath=wrapper/dists
distributionUrl=https\://services.gradle.org/distributions/gradle-8.14-bin.zip
zipStoreBase=GRADLE_USER_HOME
zipStorePath=wrapper/dists

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#!/bin/sh
#
# Copyright © 2015-2021 the original authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
##############################################################################
#
# Gradle start up script for POSIX generated by Gradle.
#
# Important for running:
#
# (1) You need a POSIX-compliant shell to run this script. If your /bin/sh is
# noncompliant, but you have some other compliant shell such as ksh or
# bash, then to run this script, type that shell name before the whole
# command line, like:
#
# ksh Gradle
#
# Busybox and similar reduced shells will NOT work, because this script
# requires all of these POSIX shell features:
# * functions;
# * expansions «$var», «${var}», «${var:-default}», «${var+SET}»,
# «${var#prefix}», «${var%suffix}», and «$( cmd )»;
# * compound commands having a testable exit status, especially «case»;
# * various built-in commands including «command», «set», and «ulimit».
#
# Important for patching:
#
# (2) This script targets any POSIX shell, so it avoids extensions provided
# by Bash, Ksh, etc; in particular arrays are avoided.
#
# The "traditional" practice of packing multiple parameters into a
# space-separated string is a well documented source of bugs and security
# problems, so this is (mostly) avoided, by progressively accumulating
# options in "$@", and eventually passing that to Java.
#
# Where the inherited environment variables (DEFAULT_JVM_OPTS, JAVA_OPTS,
# and GRADLE_OPTS) rely on word-splitting, this is performed explicitly;
# see the in-line comments for details.
#
# There are tweaks for specific operating systems such as AIX, CygWin,
# Darwin, MinGW, and NonStop.
#
# (3) This script is generated from the Groovy template
# https://github.com/gradle/gradle/blob/master/subprojects/plugins/src/main/resources/org/gradle/api/internal/plugins/unixStartScript.txt
# within the Gradle project.
#
# You can find Gradle at https://github.com/gradle/gradle/.
#
##############################################################################
# Attempt to set APP_HOME
# Resolve links: $0 may be a link
app_path=$0
# Need this for daisy-chained symlinks.
while
APP_HOME=${app_path%"${app_path##*/}"} # leaves a trailing /; empty if no leading path
[ -h "$app_path" ]
do
ls=$( ls -ld "$app_path" )
link=${ls#*' -> '}
case $link in #(
/*) app_path=$link ;; #(
*) app_path=$APP_HOME$link ;;
esac
done
APP_HOME=$( cd "${APP_HOME:-./}" && pwd -P ) || exit
APP_NAME="Gradle"
APP_BASE_NAME=${0##*/}
# Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
DEFAULT_JVM_OPTS='"-Xmx64m" "-Xms64m"'
# Use the maximum available, or set MAX_FD != -1 to use that value.
MAX_FD=maximum
warn () {
echo "$*"
} >&2
die () {
echo
echo "$*"
echo
exit 1
} >&2
# OS specific support (must be 'true' or 'false').
cygwin=false
msys=false
darwin=false
nonstop=false
case "$( uname )" in #(
CYGWIN* ) cygwin=true ;; #(
Darwin* ) darwin=true ;; #(
MSYS* | MINGW* ) msys=true ;; #(
NONSTOP* ) nonstop=true ;;
esac
CLASSPATH=$APP_HOME/gradle/wrapper/gradle-wrapper.jar
# Determine the Java command to use to start the JVM.
if [ -n "$JAVA_HOME" ] ; then
if [ -x "$JAVA_HOME/jre/sh/java" ] ; then
# IBM's JDK on AIX uses strange locations for the executables
JAVACMD=$JAVA_HOME/jre/sh/java
else
JAVACMD=$JAVA_HOME/bin/java
fi
if [ ! -x "$JAVACMD" ] ; then
die "ERROR: JAVA_HOME is set to an invalid directory: $JAVA_HOME
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
else
JAVACMD=java
which java >/dev/null 2>&1 || die "ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
Please set the JAVA_HOME variable in your environment to match the
location of your Java installation."
fi
# Increase the maximum file descriptors if we can.
if ! "$cygwin" && ! "$darwin" && ! "$nonstop" ; then
case $MAX_FD in #(
max*)
MAX_FD=$( ulimit -H -n ) ||
warn "Could not query maximum file descriptor limit"
esac
case $MAX_FD in #(
'' | soft) :;; #(
*)
ulimit -n "$MAX_FD" ||
warn "Could not set maximum file descriptor limit to $MAX_FD"
esac
fi
# Collect all arguments for the java command, stacking in reverse order:
# * args from the command line
# * the main class name
# * -classpath
# * -D...appname settings
# * --module-path (only if needed)
# * DEFAULT_JVM_OPTS, JAVA_OPTS, and GRADLE_OPTS environment variables.
# For Cygwin or MSYS, switch paths to Windows format before running java
if "$cygwin" || "$msys" ; then
APP_HOME=$( cygpath --path --mixed "$APP_HOME" )
CLASSPATH=$( cygpath --path --mixed "$CLASSPATH" )
JAVACMD=$( cygpath --unix "$JAVACMD" )
# Now convert the arguments - kludge to limit ourselves to /bin/sh
for arg do
if
case $arg in #(
-*) false ;; # don't mess with options #(
/?*) t=${arg#/} t=/${t%%/*} # looks like a POSIX filepath
[ -e "$t" ] ;; #(
*) false ;;
esac
then
arg=$( cygpath --path --ignore --mixed "$arg" )
fi
# Roll the args list around exactly as many times as the number of
# args, so each arg winds up back in the position where it started, but
# possibly modified.
#
# NB: a `for` loop captures its iteration list before it begins, so
# changing the positional parameters here affects neither the number of
# iterations, nor the values presented in `arg`.
shift # remove old arg
set -- "$@" "$arg" # push replacement arg
done
fi
# Collect all arguments for the java command;
# * $DEFAULT_JVM_OPTS, $JAVA_OPTS, and $GRADLE_OPTS can contain fragments of
# shell script including quotes and variable substitutions, so put them in
# double quotes to make sure that they get re-expanded; and
# * put everything else in single quotes, so that it's not re-expanded.
set -- \
"-Dorg.gradle.appname=$APP_BASE_NAME" \
-classpath "$CLASSPATH" \
org.gradle.wrapper.GradleWrapperMain \
"$@"
# Use "xargs" to parse quoted args.
#
# With -n1 it outputs one arg per line, with the quotes and backslashes removed.
#
# In Bash we could simply go:
#
# readarray ARGS < <( xargs -n1 <<<"$var" ) &&
# set -- "${ARGS[@]}" "$@"
#
# but POSIX shell has neither arrays nor command substitution, so instead we
# post-process each arg (as a line of input to sed) to backslash-escape any
# character that might be a shell metacharacter, then use eval to reverse
# that process (while maintaining the separation between arguments), and wrap
# the whole thing up as a single "set" statement.
#
# This will of course break if any of these variables contains a newline or
# an unmatched quote.
#
eval "set -- $(
printf '%s\n' "$DEFAULT_JVM_OPTS $JAVA_OPTS $GRADLE_OPTS" |
xargs -n1 |
sed ' s~[^-[:alnum:]+,./:=@_]~\\&~g; ' |
tr '\n' ' '
)" '"$@"'
exec "$JAVACMD" "$@"

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gradlew.bat vendored Normal file
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@rem
@rem Copyright 2015 the original author or authors.
@rem
@rem Licensed under the Apache License, Version 2.0 (the "License");
@rem you may not use this file except in compliance with the License.
@rem You may obtain a copy of the License at
@rem
@rem https://www.apache.org/licenses/LICENSE-2.0
@rem
@rem Unless required by applicable law or agreed to in writing, software
@rem distributed under the License is distributed on an "AS IS" BASIS,
@rem WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
@rem See the License for the specific language governing permissions and
@rem limitations under the License.
@rem
@if "%DEBUG%" == "" @echo off
@rem ##########################################################################
@rem
@rem Gradle startup script for Windows
@rem
@rem ##########################################################################
@rem Set local scope for the variables with windows NT shell
if "%OS%"=="Windows_NT" setlocal
set DIRNAME=%~dp0
if "%DIRNAME%" == "" set DIRNAME=.
set APP_BASE_NAME=%~n0
set APP_HOME=%DIRNAME%
@rem Resolve any "." and ".." in APP_HOME to make it shorter.
for %%i in ("%APP_HOME%") do set APP_HOME=%%~fi
@rem Add default JVM options here. You can also use JAVA_OPTS and GRADLE_OPTS to pass JVM options to this script.
set DEFAULT_JVM_OPTS="-Xmx64m" "-Xms64m"
@rem Find java.exe
if defined JAVA_HOME goto findJavaFromJavaHome
set JAVA_EXE=java.exe
%JAVA_EXE% -version >NUL 2>&1
if "%ERRORLEVEL%" == "0" goto execute
echo.
echo ERROR: JAVA_HOME is not set and no 'java' command could be found in your PATH.
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:findJavaFromJavaHome
set JAVA_HOME=%JAVA_HOME:"=%
set JAVA_EXE=%JAVA_HOME%/bin/java.exe
if exist "%JAVA_EXE%" goto execute
echo.
echo ERROR: JAVA_HOME is set to an invalid directory: %JAVA_HOME%
echo.
echo Please set the JAVA_HOME variable in your environment to match the
echo location of your Java installation.
goto fail
:execute
@rem Setup the command line
set CLASSPATH=%APP_HOME%\gradle\wrapper\gradle-wrapper.jar
@rem Execute Gradle
"%JAVA_EXE%" %DEFAULT_JVM_OPTS% %JAVA_OPTS% %GRADLE_OPTS% "-Dorg.gradle.appname=%APP_BASE_NAME%" -classpath "%CLASSPATH%" org.gradle.wrapper.GradleWrapperMain %*
:end
@rem End local scope for the variables with windows NT shell
if "%ERRORLEVEL%"=="0" goto mainEnd
:fail
rem Set variable GRADLE_EXIT_CONSOLE if you need the _script_ return code instead of
rem the _cmd.exe /c_ return code!
if not "" == "%GRADLE_EXIT_CONSOLE%" exit 1
exit /b 1
:mainEnd
if "%OS%"=="Windows_NT" endlocal
:omega

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rootProject.name = "GAN"

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src/main/java/Main.java Normal file
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import domain.annealing.SimulatedAnnealing;
import domain.ant_colony.AntColonyOptimization;
import domain.binary.algorithm.SimpleGeneticAlgorithm;
import java.util.Scanner;
public class Main {
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
System.out.println("Run algorithm:");
System.out.println("1 - Simulated Annealing");
System.out.println("2 - Simple Genetic Algorithm");
System.out.println("3 - Ant Colony");
int decision = in.nextInt();
switch (decision) {
case 1:
System.out.println("Optimized distance for travel: " + SimulatedAnnealing.simulateAnnealing(10, 10000, 0.9995));
break;
case 2:
SimpleGeneticAlgorithm ga = new SimpleGeneticAlgorithm(
0.5,
0.025,
5,
true,
new byte[64]
);
ga.runAlgorithm(50, "1011000100000100010000100000100111001000000100000100000000001111");
break;
case 3:
AntColonyOptimization antColony = new AntColonyOptimization(21);
antColony.startAntOptimization();
break;
default:
System.out.println("Unknown option");
break;
}
in.close();
}
}

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src/main/java/domain/annealing/City.java Normal file
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package domain.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));
}
}

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src/main/java/domain/annealing/SimulatedAnnealing.java Normal file
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package domain.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;
}
}

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src/main/java/domain/annealing/Travel.java Normal file
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package domain.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;
}
}

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src/main/java/domain/ant_colony/Ant.java Normal file
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package domain.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;
}
}

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src/main/java/domain/ant_colony/AntColonyOptimization.java Normal file
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package domain.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);
});
}
}

52
src/main/java/domain/binary/Individual.java Normal file
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package domain.binary;
import domain.binary.algorithm.SimpleGeneticAlgorithm;
import lombok.Data;
@Data
public class Individual {
protected int defaultGeneLength = 64;
private byte[] genes = new byte[defaultGeneLength];
private int fitness = 0;
public Individual(byte[] solution) {
for (int i = 0; i < genes.length; i++) {
byte gene = (byte) Math.round(Math.random());
genes[i] = gene;
}
this.fitness = computeFitness(solution);
}
public byte getSingleGene(int index) {
return genes[index];
}
public void setSingleGene(int index, byte value) {
genes[index] = value;
fitness = 0;
}
public void recomputeFitness(byte[] solution) {
this.fitness = computeFitness(solution);
}
private int computeFitness(byte[] solution) {
int fitness = 0;
for (int i = 0; i < this.getDefaultGeneLength() && i < solution.length; i++) {
if (this.getSingleGene(i) != solution[i]) continue;
fitness++;
}
return fitness;
}
@Override
public String toString() {
StringBuilder geneString = new StringBuilder();
for (int i = 0; i < genes.length; i++) {
geneString.append(getSingleGene(i));
}
return geneString.toString();
}
}

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package domain.binary;
import java.util.ArrayList;
import java.util.List;
import lombok.Data;
@Data
public class Population {
private final int size;
private final int tournamentSize;
private final double mutationRate;
private final double uniformRate;
private Individual[] individuals;
public Population(
int size,
double uniformRate,
double mutationRate,
int tournamentSize,
byte[] solution
) {
this(size, uniformRate, mutationRate, tournamentSize);
this.individuals = createNewPopulation(size, solution);
}
private Population(
int size,
double uniformRate,
double mutationRate,
int tournamentSize
) {
this.size = size;
this.uniformRate = uniformRate;
this.mutationRate = mutationRate;
this.tournamentSize = tournamentSize;
individuals = new Individual[size];
}
public Individual getIndividual(int index) {
return individuals[index];
}
public Individual setIndividual(int index, Individual individual) {
return individuals[index] = individual;
}
public Individual getFittest() {
Individual fittest = individuals[0];
for (int i = 0; i < individuals.length; i++) {
if (fittest.getFitness() <= getIndividual(i).getFitness()) {
fittest = getIndividual(i);
}
}
return fittest;
}
public Population evolve(boolean withElitism, byte[] solution) {
int elitismOffset;
Individual[] newIndividuals = new Individual[size];
if (withElitism) {
newIndividuals[0] = getFittest();
elitismOffset = 1;
} else {
elitismOffset = 0;
}
for (int i = elitismOffset; i < getIndividuals().length; i++) {
Individual indiv1 = tournamentSelection();
Individual indiv2 = tournamentSelection();
Individual newIndiv = crossover(indiv1, indiv2, solution);
newIndividuals[i] = newIndiv;
}
for (int i = elitismOffset; i < newIndividuals.length; i++) {
mutate(newIndividuals[i]);
newIndividuals[i].recomputeFitness(solution);
}
Population newPop = this.copy();
newPop.setIndividuals(newIndividuals);
return newPop;
}
private Individual crossover(Individual indiv1, Individual indiv2, byte[] solution) {
Individual newSol = new Individual(solution);
for (int i = 0; i < newSol.getDefaultGeneLength(); i++) {
newSol.setSingleGene(i, Math.random() <= uniformRate
? indiv1.getSingleGene(i)
: indiv2.getSingleGene(i));
}
newSol.recomputeFitness(solution);
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 tournament = this.copy();
for (int i = 0; i < tournamentSize; i++) {
int randomId = (int) (Math.random() * this.getIndividuals().length);
tournament.setIndividual(i, this.getIndividual(randomId));
}
return tournament.getFittest();
}
private Individual[] createNewPopulation(int size, byte[] solution) {
Individual[] newIndividuals = new Individual[size];
for (int i = 0; i < size; i++) {
Individual newIndividual = new Individual(solution);
newIndividuals[i] = newIndividual;
}
return newIndividuals;
}
public Population copy() {
Population p = new Population(size, uniformRate, mutationRate, tournamentSize);
p.setIndividuals(this.individuals);
return p;
}
}

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src/main/java/domain/binary/algorithm/CustomGeneticAlgorithm.java Normal file
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package domain.binary.algorithm;
import domain.binary.Population;
public class CustomGeneticAlgorithm extends SimpleGeneticAlgorithm {
public CustomGeneticAlgorithm(
double uniformRate,
double mutationRate,
int tournamentSize,
boolean elitism,
byte[] solution
) {
super(uniformRate, mutationRate, tournamentSize, elitism, solution);
}
@Override
public boolean runAlgorithm(int populationSize, String solution){
return false;
}
@Override
public boolean checkStopCriteria(Population pop) {
return false;
}
}

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src/main/java/domain/binary/algorithm/SimpleGeneticAlgorithm.java Normal file
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package domain.binary.algorithm;
import domain.binary.Individual;
import domain.binary.Population;
import lombok.Data;
@Data
public class SimpleGeneticAlgorithm {
private final double uniformRate;
private final double mutationRate;
private final int tournamentSize;
private final boolean elitism;
private byte[] solution;
public SimpleGeneticAlgorithm(
double uniformRate,
double mutationRate,
int tournamentSize,
boolean elitism,
byte[] solution
){
this.uniformRate = uniformRate;
this.mutationRate = mutationRate;
this.tournamentSize = tournamentSize;
this.elitism = elitism;
this.solution = solution;
}
public boolean runAlgorithm(int populationSize, String solution) {
setSolution(solution);
Population myPop = new Population(
populationSize,
uniformRate,
mutationRate,
tournamentSize,
this.solution);
int generationCount = 1;
while (checkStopCriteria(myPop)) {
System.out.println("Generation: " + generationCount + " Correct genes found: " + myPop.getFittest().getFitness());
myPop = myPop.evolve(elitism, this.solution);
generationCount++;
}
System.out.println("Solution found!");
System.out.println("Generation: " + generationCount);
System.out.println("Genes: ");
System.out.println(myPop.getFittest());
return true;
}
public boolean checkStopCriteria(Population pop) {
int fitness = pop.getFittest().getFitness();
int maxFitness = getMaxFitness();
return fitness < maxFitness;
}
protected int getMaxFitness() {
int maxFitness = solution.length;
return maxFitness;
}
protected void setSolution(String newSolution) {
if (newSolution.length() != this.solution.length) {
throw new RuntimeException("The solution needs to have " + this.solution.length + " bytes");
}
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;
}
}
}
}

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src/main/java/domain/jenetics/Knapsack.java Normal file
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package domain.jenetics;
import io.jenetics.*;
import io.jenetics.engine.Engine;
import io.jenetics.engine.EvolutionStatistics;
import java.util.stream.Stream;
import static io.jenetics.engine.EvolutionResult.toBestPhenotype;
import static io.jenetics.engine.Limits.bySteadyFitness;
public class Knapsack {
public static void main(String[] args) {
int nItems = 15;
double ksSize = nItems * 100.0 / 3.0;
KnapsackFF ff = new KnapsackFF(Stream.generate(KnapsackItem::random)
.limit(nItems)
.toArray(KnapsackItem[]::new), ksSize);
Engine<BitGene, Double> engine = Engine.builder(ff, BitChromosome.of(nItems, 0.5))
.populationSize(500)
.survivorsSelector(new TournamentSelector<>(5))
.offspringSelector(new RouletteWheelSelector<>())
.alterers(new Mutator<>(0.115), new SinglePointCrossover<>(0.16))
.build();
EvolutionStatistics<Double, ?> statistics = EvolutionStatistics.ofNumber();
Phenotype<BitGene, Double> best = engine.stream()
.limit(bySteadyFitness(7))
.limit(100)
.peek(statistics)
.collect(toBestPhenotype());
System.out.println(statistics);
System.out.println(best);
}
}

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src/main/java/domain/jenetics/KnapsackFF.java Normal file
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package domain.jenetics;
import io.jenetics.BitChromosome;
import io.jenetics.BitGene;
import io.jenetics.Genotype;
import java.util.function.Function;
public class KnapsackFF implements Function<Genotype<BitGene>, Double> {
private KnapsackItem[] items;
private double size;
public KnapsackFF(KnapsackItem[] items, double size) {
this.items = items;
this.size = size;
}
@Override
public Double apply(Genotype<BitGene> gt) {
KnapsackItem sum = ((BitChromosome) gt.getChromosome()).ones()
.mapToObj(i -> items[i])
.collect(KnapsackItem.toSum());
return sum.size <= this.size ? sum.value : 0;
}
}

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src/main/java/domain/jenetics/KnapsackItem.java Normal file
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package domain.jenetics;
import io.jenetics.util.RandomRegistry;
import java.util.Random;
import java.util.stream.Collector;
public class KnapsackItem {
public double size;
public double value;
public KnapsackItem(double size, double value) {
this.size = size;
this.value = value;
}
protected static KnapsackItem random() {
Random r = RandomRegistry.getRandom();
return new KnapsackItem(r.nextDouble() * 100, r.nextDouble() * 100);
}
protected static Collector<KnapsackItem, ?, KnapsackItem> toSum() {
return Collector.of(() -> new double[2], (a, b) -> {
a[0] += b.size;
a[1] += b.value;
} , (a, b) -> {
a[0] += b[0];
a[1] += b[1];
return a;
} , r -> new KnapsackItem(r[0], r[1]));
}
}

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src/main/java/domain/jenetics/SimpleGeneticAlgorithm.java Normal file
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package domain.jenetics;
import io.jenetics.BitChromosome;
import io.jenetics.BitGene;
import io.jenetics.Genotype;
import io.jenetics.engine.Engine;
import io.jenetics.engine.EvolutionResult;
import io.jenetics.util.Factory;
public class SimpleGeneticAlgorithm {
private static Integer eval(Genotype<BitGene> gt) {
return gt.getChromosome()
.as(BitChromosome.class)
.bitCount();
}
public static void main(String[] args) {
Factory<Genotype<BitGene>> gtf = Genotype.of(BitChromosome.of(10, 0.5));
System.out.println("Before the evolution:\n" + gtf);
Engine<BitGene, Integer> engine = Engine.builder(SimpleGeneticAlgorithm::eval, gtf)
.build();
Genotype<BitGene> result = engine.stream()
.limit(500)
.collect(EvolutionResult.toBestGenotype());
System.out.println("After the evolution:\n" + result);
}
}

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src/main/java/domain/jenetics/SpringsteenProblem.java Normal file
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package domain.jenetics;
import io.jenetics.BitGene;
import io.jenetics.engine.*;
import io.jenetics.util.ISeq;
import static java.util.Objects.requireNonNull;
import java.util.function.Function;
import java.util.stream.Collectors;
public class SpringsteenProblem implements Problem<ISeq<SpringsteenRecord>, BitGene, Double> {
private ISeq<SpringsteenRecord> records;
private double maxPricePerUniqueSong;
public SpringsteenProblem(ISeq<SpringsteenRecord> records, double maxPricePerUniqueSong) {
this.records = requireNonNull(records);
this.maxPricePerUniqueSong = maxPricePerUniqueSong;
}
@Override
public Function<ISeq<SpringsteenRecord>, Double> fitness() {
return SpringsteenRecords -> {
double cost = SpringsteenRecords.stream()
.mapToDouble(r -> r.price)
.sum();
int uniqueSongCount = SpringsteenRecords.stream()
.flatMap(r -> r.songs.stream())
.collect(Collectors.toSet())
.size();
double pricePerUniqueSong = cost / uniqueSongCount;
return pricePerUniqueSong <= maxPricePerUniqueSong ? uniqueSongCount : 0.0;
};
}
@Override
public Codec<ISeq<SpringsteenRecord>, BitGene> codec() {
return Codecs.ofSubSet(records);
}
public static void main(String[] args) {
double maxPricePerUniqueSong = 2.5;
SpringsteenProblem springsteen = new SpringsteenProblem(
ISeq.of(new SpringsteenRecord("SpringsteenRecord1", 25, ISeq.of("Song1", "Song2", "Song3", "Song4", "Song5", "Song6")), new SpringsteenRecord("SpringsteenRecord2", 15, ISeq.of("Song2", "Song3", "Song4", "Song5", "Song6", "Song7")),
new SpringsteenRecord("SpringsteenRecord3", 35, ISeq.of("Song5", "Song6", "Song7", "Song8", "Song9", "Song10")), new SpringsteenRecord("SpringsteenRecord4", 17, ISeq.of("Song9", "Song10", "Song12", "Song4", "Song13", "Song14")),
new SpringsteenRecord("SpringsteenRecord5", 29, ISeq.of("Song1", "Song2", "Song13", "Song14", "Song15", "Song16")), new SpringsteenRecord("SpringsteenRecord6", 5, ISeq.of("Song18", "Song20", "Song30", "Song40"))),
maxPricePerUniqueSong);
Engine<BitGene, Double> engine = Engine.builder(springsteen)
.build();
ISeq<SpringsteenRecord> result = springsteen.codec()
.decoder()
.apply(engine.stream()
.limit(10)
.collect(EvolutionResult.toBestGenotype()));
double cost = result.stream()
.mapToDouble(r -> r.price)
.sum();
int uniqueSongCount = result.stream()
.flatMap(r -> r.songs.stream())
.collect(Collectors.toSet())
.size();
double pricePerUniqueSong = cost / uniqueSongCount;
System.out.println("Overall cost: " + cost);
System.out.println("Unique songs: " + uniqueSongCount);
System.out.println("Cost per song: " + pricePerUniqueSong);
System.out.println("Records: " + result.map(r -> r.name)
.toString(", "));
}
}

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src/main/java/domain/jenetics/SpringsteenRecord.java Normal file
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package domain.jenetics;
import static java.util.Objects.requireNonNull;
import io.jenetics.util.ISeq;
import lombok.Data;
import lombok.NoArgsConstructor;
@Data
@NoArgsConstructor
public class SpringsteenRecord {
String name;
double price;
ISeq<String> songs;
public SpringsteenRecord(String name, double price, ISeq<String> songs) {
this.name = requireNonNull(name);
this.price = price;
this.songs = requireNonNull(songs);
}
}

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src/main/java/domain/jenetics/TravelingSalesman.java Normal file
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package domain.jenetics;
import io.jenetics.*;
import io.jenetics.engine.Codecs;
import io.jenetics.engine.Engine;
import io.jenetics.engine.EvolutionStatistics;
import static io.jenetics.engine.EvolutionResult.toBestPhenotype;
import static io.jenetics.engine.Limits.bySteadyFitness;
import static java.lang.Math.PI;
import static java.lang.Math.abs;
import static java.lang.Math.sin;
import java.util.stream.IntStream;
public class TravelingSalesman {
private static final int STOPS = 50;
private static final double[][] ADJACENCE = matrix(STOPS);
private static double[][] matrix(int stops) {
final double radius = 100.0;
double[][] matrix = new double[stops][stops];
for (int i = 0; i < stops; ++i) {
for (int j = 0; j < stops; ++j) {
matrix[i][j] = chord(stops, abs(i - j), radius);
}
}
return matrix;
}
private static double chord(int stops, int i, double r) {
return 2.0 * r * abs(sin(PI * i / stops));
}
private static double dist(final int[] path) {
return IntStream.range(0, STOPS)
.mapToDouble(i -> ADJACENCE[path[i]][path[(i + 1) % STOPS]])
.sum();
}
public static void main(String[] args) {
final Engine<EnumGene<Integer>, Double> engine = Engine.builder(TravelingSalesman::dist, Codecs.ofPermutation(STOPS))
.optimize(Optimize.MINIMUM)
.maximalPhenotypeAge(11)
.populationSize(500)
.alterers(new SwapMutator<>(0.2), new PartiallyMatchedCrossover<>(0.35))
.build();
final EvolutionStatistics<Double, ?> statistics = EvolutionStatistics.ofNumber();
final Phenotype<EnumGene<Integer>, Double> best = engine.stream()
.limit(bySteadyFitness(15))
.limit(250)
.peek(statistics)
.collect(toBestPhenotype());
System.out.println(statistics);
System.out.println(best);
}
}