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January 6, 2013 22:26
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import java.io.BufferedWriter; | |
import java.io.File; | |
import java.io.FileWriter; | |
import java.io.IOException; | |
import java.util.ArrayList; | |
import java.util.Collections; | |
import java.util.Random; | |
import java.util.Scanner; | |
public class GeneticKnapsackAlgorithm { | |
private static ArrayList<Specimen> genePool; | |
private static ArrayList<Specimen> childrenPopulation; | |
//Change these to tweak runtime | |
private static final int genePoolSize = 50; | |
private static final int numGenerations = 1000; | |
private static final int numChildren = 50; | |
private static int bestPossibleFitness; | |
private static Random rGen; | |
private static int numItems; | |
private static int knapsackWidth; | |
private static int knapsackLength; | |
//Prints the most-fit specimen of the genePool to a file | |
public static void printToFile() | |
{ | |
Specimen mostFit; | |
File outFile; | |
BufferedWriter writer; | |
mostFit = getMostFit(genePool); | |
outFile = new File("Most fit Pack-O-Tron Specimen.txt"); | |
try | |
{ | |
writer = new BufferedWriter(new FileWriter(outFile)); | |
writer.write("Fitness: " + mostFit.getFitness()); | |
writer.newLine(); | |
for(KnapsackObject object : mostFit.getObjectArray()) | |
{ | |
writer.write(object.getWidth() + " " + object.getLength()); | |
writer.newLine(); | |
} | |
for(int j = 0; j < knapsackLength; j++) | |
{ | |
for(int i = 0; i < knapsackWidth; i++) | |
{ | |
writer.write(mostFit.getKnapsack()[i][j] + " "); | |
} | |
writer.newLine(); | |
} | |
writer.close(); | |
} catch (IOException e) { | |
// Who cares | |
e.printStackTrace(); | |
} | |
} | |
/* Used for testing purposed */ | |
public static void printSpecimenToFile(Specimen specimen) | |
{ | |
File outFile; | |
BufferedWriter writer; | |
outFile = new File("Pack-O-Tron Test Specimen.txt"); | |
try | |
{ | |
writer = new BufferedWriter(new FileWriter(outFile)); | |
writer.write("Fitness: " + specimen.getFitness()); | |
writer.newLine(); | |
for(KnapsackObject object : specimen.getObjectArray()) | |
{ | |
writer.write(object.getWidth() + " " + object.getLength()); | |
writer.newLine(); | |
} | |
for(int j = 0; j < knapsackLength; j++) | |
{ | |
for(int i = 0; i < knapsackWidth; i++) | |
{ | |
writer.write(specimen.getKnapsack()[i][j] + " "); | |
} | |
writer.newLine(); | |
} | |
writer.close(); | |
} catch (IOException e) { | |
// Who cares | |
e.printStackTrace(); | |
} | |
} | |
/* Similar to writeToFile(), but prints to console instead */ | |
public static void printResult() | |
{ | |
Specimen mostFit; | |
mostFit = getMostFit(genePool); | |
System.out.println("Fitness: " + mostFit.getFitness()); | |
for(KnapsackObject object : mostFit.getObjectArray()) | |
System.out.println(object.getWidth() + " " + object.getLength()); | |
for(int j = 0; j < mostFit.getKnapsack()[0].length; j++) | |
{ | |
for(int i = 0; i < mostFit.getKnapsack().length; i++) | |
{ | |
System.out.printf("%d ", mostFit.getKnapsack()[i][j]); | |
} | |
System.out.println(); | |
} | |
} | |
/* Returns the most-fit Specimen of some pool | |
* Used for genePool improvement. | |
*/ | |
public static Specimen getMostFit(ArrayList<Specimen> pool) | |
{ | |
Specimen mostFit; | |
mostFit = pool.get(0); | |
for(Specimen specimen : pool) | |
{ | |
if(specimen.getFitness() < mostFit.getFitness()) | |
mostFit = specimen; | |
} | |
return mostFit; | |
} | |
/* Returns the second-most-fit Specimen of some pool | |
* Used for genePool improvement. | |
*/ | |
public static Specimen getSecondMostFit(ArrayList<Specimen> pool) | |
{ | |
Specimen mostFit; | |
Specimen secondMostFit; | |
mostFit = getMostFit(pool); | |
if(pool.get(0) == mostFit) | |
secondMostFit = pool.get(1); | |
else | |
secondMostFit = pool.get(0); | |
for(Specimen specimen : pool) | |
{ | |
if(specimen.getFitness() < secondMostFit.getFitness() && specimen != mostFit) | |
secondMostFit = specimen; | |
} | |
return secondMostFit; | |
} | |
/* Returns the least-fit Specimen of some pool | |
* Used for genePool improvement. | |
*/ | |
public static Specimen getLeastFit(ArrayList<Specimen> pool) | |
{ | |
Specimen leastFit; | |
leastFit = pool.get(0); | |
for(Specimen specimen : pool) | |
{ | |
if(specimen.getFitness() > leastFit.getFitness()) | |
leastFit = specimen; | |
} | |
return leastFit; | |
} | |
/* Returns the second-least-fit Specimen of some pool | |
* Used for genePool improvement. | |
*/ | |
public static Specimen getSecondLeastFit(ArrayList<Specimen> pool) | |
{ | |
Specimen leastFit; | |
Specimen secondLeastFit; | |
leastFit = getLeastFit(pool); | |
if(pool.get(0) == leastFit) | |
secondLeastFit = pool.get(1); | |
else | |
secondLeastFit = pool.get(0); | |
for(Specimen specimen : pool) | |
{ | |
if(specimen.getFitness() > secondLeastFit.getFitness() && specimen != leastFit) | |
secondLeastFit = specimen; | |
} | |
return secondLeastFit; | |
} | |
/* Initializes the genePool with the array of objects */ | |
public static void initializeGenePool(ArrayList<KnapsackObject> objectArray) | |
{ | |
genePool = new ArrayList<Specimen>(); | |
bestPossibleFitness = 0; | |
//The best possible bounding box area is the sum of all of the object's areas. This might not be possible to achieve. | |
for(KnapsackObject object : objectArray) | |
bestPossibleFitness += object.getArea(); | |
for(int i = 0; i < genePoolSize; i++) | |
{ | |
genePool.add(new Specimen(knapsackWidth, knapsackLength, numItems, objectArray, true)); | |
//genePool.get(i).determineFitness() (Now called in constructor) | |
} | |
} | |
/* Creates a new "genome", or ordered list, based off of two parents */ | |
public static Specimen mutateGenome(Specimen parent1, Specimen parent2) | |
{ | |
Specimen child; | |
Specimen tempSpecimen; | |
boolean dominantParent; | |
KnapsackObject chosenTrait; | |
int indexOfTrait; | |
int indexInOtherParent; | |
ArrayList<KnapsackObject> tempList; | |
int mutationChance; | |
dominantParent = rGen.nextBoolean(); | |
mutationChance = rGen.nextInt(100) + 1; | |
if(dominantParent) //Randomly determines the "dominant" parent | |
{ | |
tempSpecimen = parent1; | |
parent1 = parent2; | |
parent2 = parent1; | |
} | |
//Copies a "gene"'s, or KnapsackObject's, position from one parent to another, resulting in a new "genome" | |
indexOfTrait = rGen.nextInt(numItems); | |
chosenTrait = parent1.getObjectArray().get(indexOfTrait); | |
tempList = new ArrayList<KnapsackObject>(); | |
//tempList.addAll(0, parent2.getObjectArray()); | |
tempList = parent2.getObjectArray(); | |
indexInOtherParent = tempList.indexOf(chosenTrait); | |
tempList.remove(indexInOtherParent); | |
tempList.add(indexOfTrait, chosenTrait); | |
//Randomly swaps two object's positions | |
if(mutationChance % 7 == 0) | |
{ | |
int randomIndex1; | |
int randomIndex2; | |
KnapsackObject object1; | |
KnapsackObject object2; | |
randomIndex1 = rGen.nextInt(numItems); | |
do | |
{ | |
randomIndex2 = rGen.nextInt(numItems); | |
} while(randomIndex1 == randomIndex2); | |
object1 = tempList.get(randomIndex1); | |
object2 = tempList.get(randomIndex2); | |
tempList.set(randomIndex1, object2); | |
tempList.set(randomIndex2, object1); | |
} | |
//Randomly reverses the array | |
if(mutationChance < 15) | |
{ | |
Collections.reverse(tempList); | |
} | |
//Randomly swaps the sides of an object in the array | |
if(mutationChance % 14 == 0) | |
{ | |
KnapsackObject tempObject; | |
int randomIndex; | |
randomIndex = rGen.nextInt(numItems); | |
tempObject = tempList.get(randomIndex); | |
tempObject.swapSides(); | |
tempList.set(randomIndex, tempObject); | |
} | |
child = new Specimen(knapsackWidth, knapsackLength, numItems, tempList, false); | |
return child; | |
} | |
/* Generates a pool of children based off of two parents */ | |
public static void generateChildren(Specimen parent1, Specimen parent2) | |
{ | |
childrenPopulation = new ArrayList<Specimen>(); //Resets the child pool | |
for(int i = 0; i < numChildren; i++) | |
childrenPopulation.add(mutateGenome(parent1, parent2)); | |
} | |
/* Determines whether or not to replace individuals in the genePool with children, based on fitness */ | |
public static boolean compete() | |
{ | |
boolean returnValue; | |
Specimen genePoolLeastFit; | |
Specimen genePoolSecondLeastFit; | |
Specimen childStrongest; | |
Specimen childSecondStrongest; | |
returnValue = false; | |
genePoolLeastFit = getLeastFit(genePool); | |
genePoolSecondLeastFit = getSecondLeastFit(genePool); | |
childStrongest = getMostFit(childrenPopulation); | |
childSecondStrongest = getSecondMostFit(childrenPopulation); | |
if(childSecondStrongest.getFitness() < genePoolSecondLeastFit.getFitness()) //If the "weakest" strong child is stronger than the strongest "weak" genePool member, swap both | |
{ | |
genePool.set(genePool.indexOf(genePoolSecondLeastFit), childSecondStrongest); | |
genePool.set(genePool.indexOf(genePoolLeastFit), childStrongest); | |
returnValue = true; | |
} | |
//Otherwise, replace the weakest Specimen in the genePool with the strongest child. | |
else if(childStrongest.getFitness() < genePoolLeastFit.getFitness()) | |
{ | |
genePool.set(genePool.indexOf(genePoolLeastFit), childStrongest); | |
returnValue = true; | |
} | |
return returnValue; //A replacement occured | |
} | |
/* Selects two parents and updates the genePool */ | |
public static void evolve() | |
{ | |
int matingType; | |
boolean randomChoice; | |
Specimen parent1; | |
Specimen parent2; | |
int parent1Index; | |
int parent2Index; | |
matingType = rGen.nextInt(99); | |
if(matingType < 33) //Two random parents | |
{ | |
parent1Index = rGen.nextInt(genePool.size()); | |
do | |
{ | |
parent2Index = rGen.nextInt(genePool.size()); | |
} while(parent1Index == parent2Index); | |
parent1 = genePool.get(parent1Index); | |
parent2 = genePool.get(parent2Index); | |
} | |
else if(matingType < 67) //Two most fit parents | |
{ | |
parent1 = getMostFit(genePool); | |
parent2 = getSecondMostFit(genePool); | |
} | |
else //One of the most fit parents and a random parent | |
{ | |
randomChoice = rGen.nextBoolean(); | |
if(randomChoice) | |
parent1 = getMostFit(genePool); | |
else | |
parent1 = getSecondMostFit(genePool); | |
parent1Index = genePool.indexOf(parent1); | |
do | |
{ | |
parent2Index = rGen.nextInt(genePool.size()); | |
} while(parent1Index == parent2Index); | |
parent2 = genePool.get(parent2Index); | |
} | |
generateChildren(parent1, parent2); | |
} | |
/* Genetic "master" function. Call this to start the genetic process */ | |
public static void darwinize() | |
{ | |
int currentGeneration; | |
currentGeneration = 0; | |
printToFile(); //Writes the current-best Specimen to a file | |
//If the best possible fit has been found, stop. Otherwise, continue until specified number of generations | |
while((getMostFit(genePool).getFitness() != bestPossibleFitness) && (currentGeneration < numGenerations)) | |
{ | |
currentGeneration++; | |
System.out.println("Generation " + currentGeneration); | |
evolve(); | |
if(compete()) | |
{ | |
System.out.println("Generation improved!"); | |
} | |
} | |
printToFile(); //Updates the best speciment. | |
} | |
/* Used for testing purposes */ | |
public static void testSpecimen(ArrayList<KnapsackObject> objectArray) | |
{ | |
Specimen sample; | |
sample = new Specimen(knapsackWidth, knapsackLength, numItems, objectArray, false); | |
printSpecimenToFile(sample); | |
} | |
public static void main(String [] args) | |
{ | |
Scanner input; | |
ArrayList<KnapsackObject> objectArray; | |
String tempInput; | |
String [] tempInputArray; | |
input = new Scanner(System.in); | |
rGen = new Random(); | |
tempInput = input.nextLine(); | |
tempInputArray = tempInput.split(" "); | |
knapsackWidth = Integer.parseInt(tempInputArray[0]); | |
knapsackLength = Integer.parseInt(tempInputArray[1]); | |
numItems = input.nextInt(); | |
objectArray = new ArrayList<KnapsackObject>(); | |
input.nextLine(); //Takes care of trailing /n | |
for(int i = 0; i < numItems; i++) | |
{ | |
tempInput = input.nextLine(); | |
tempInputArray = tempInput.split(" "); | |
objectArray.add(new KnapsackObject(Integer.parseInt(tempInputArray[0]), Integer.parseInt(tempInputArray[1]))); | |
} | |
//testSpecimen(objectArray); (Testing purposes) | |
initializeGenePool(objectArray); | |
darwinize(); | |
} | |
} |
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/* Rectangles. | |
* | |
*/ | |
public class KnapsackObject { | |
private int width; | |
private int length; | |
private int area; | |
public KnapsackObject(int width, int length) | |
{ | |
this.width = width; | |
this.length = length; | |
updateArea(); | |
} | |
public int getWidth() | |
{ | |
return width; | |
} | |
public int getLength() | |
{ | |
return length; | |
} | |
public void setWidth(int width) | |
{ | |
this.width = width; | |
updateArea(); | |
} | |
public void setLength(int length) | |
{ | |
this.length = length; | |
updateArea(); | |
} | |
private void updateArea() | |
{ | |
area = width * length; | |
} | |
public int getArea() | |
{ | |
return area; | |
} | |
public void swapSides() | |
{ | |
int temp; | |
temp = width; | |
width = length; | |
length = temp; | |
} | |
//Initially wanted to implement Comparable. Not needed. | |
/* | |
public int compareTo(Object comparator) | |
{ | |
final int smaller = -1; | |
final int equal = 0; | |
final int larger = 1; | |
if(this == comparator) | |
return equal; | |
else if(this.getArea() < ((KnapsackObject) comparator).getArea()) | |
return smaller; | |
else | |
return larger; | |
} | |
*/ | |
} |
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/* A Specimen is a knapsack packed with an ordered list of objects using a first-fit algorithm. | |
* | |
*/ | |
import java.util.ArrayList; | |
import java.util.Random; | |
public class Specimen{ | |
private int [][] knapsack; | |
private int numItems; | |
private ArrayList<KnapsackObject> objectArray; | |
private int fitness; | |
/* Constructor. Creates a Specimen with a given knapsack size, number of objects, list of objects, and whether or not the object order is random */ | |
public Specimen(int knapsackWidth, int knapsackLength, int numItems, ArrayList<KnapsackObject> objectArray, boolean random) | |
{ | |
knapsack = new int[knapsackWidth][knapsackLength]; | |
this.numItems = numItems; | |
//The object order isn't random. Keep the list as-is. | |
if(!random) | |
{ | |
this.objectArray = objectArray; | |
} | |
//The object order is random. Randomize both the order of the list and the orientation of objects. | |
else //Randomly sets up objectArray; | |
{ | |
Random rGen; | |
boolean swapSides; | |
int currentPosition; | |
ArrayList<Integer> usedArrayPositions; | |
KnapsackObject [] tempArray; | |
KnapsackObject tempObject; | |
rGen = new Random(); | |
swapSides = false; | |
usedArrayPositions = new ArrayList<Integer>(); | |
tempArray = new KnapsackObject[objectArray.size()]; | |
this.objectArray = new ArrayList<KnapsackObject>(); | |
//Randomly orders objects | |
for(int i = 0; i < numItems; i++) | |
{ | |
swapSides = rGen.nextBoolean(); | |
do | |
{ | |
currentPosition = rGen.nextInt(numItems); | |
} while(usedArrayPositions.contains(currentPosition)); | |
usedArrayPositions.add(currentPosition); | |
tempObject = objectArray.get(i); | |
//Randomly orients objects | |
if(swapSides) | |
tempObject.swapSides(); | |
tempArray[currentPosition] = tempObject; | |
} | |
//Initializes objectArray with this new random ordering | |
for(int i = 0; i < numItems; i++) | |
this.objectArray.add(tempArray[i]); | |
} | |
//Updates fitness (packs the knapsack) | |
fitness = 0; | |
determineFitness(); | |
} | |
public void print() | |
{ | |
System.out.println(); | |
for(int j = 0; j < knapsack[0].length; j++) | |
{ | |
for(int i = 0; i < knapsack.length; i++) | |
{ | |
System.out.print(knapsack[i][j]+ " "); | |
} | |
System.out.println(); | |
} | |
} | |
/* Updates the knapsack with an object and it's starting position. Should only be called from tryToFit(), which should only be called from pack() */ | |
private void placeObject(int startX, int startY, int width, int length, int positionInArray) | |
{ | |
positionInArray++; //Passed the actual index, 0-based. Converts to 1-based. | |
for(int j = 0; j < length; j++) | |
{ | |
for(int i = 0; i < width; i++) | |
{ | |
//System.out.println("Writing " + positionInArray + " to " + i + " " + j); | |
knapsack[startX + i][startY + j] = positionInArray; | |
} | |
} | |
} | |
/* Fairly naive approach. Attemps to fit some object in the knapsack in the upper-left-most corner. | |
* Moves right and then wraps around (x = 0, y++) looking for possible spots to place the item. | |
*/ | |
private boolean tryToFit(KnapsackObject object, int indexInArray) | |
{ | |
boolean canFit; | |
canFit = true; | |
for(int j = 0; j < knapsack[0].length; j++) | |
{ | |
for(int i = 0; i < knapsack.length; i++) | |
{ | |
for(int m = 0; m < object.getLength(); m++) | |
{ | |
for(int n = 0; n < object.getWidth(); n++) | |
{ | |
if( (i + n >= knapsack.length) || (j + m >= knapsack[0].length) || (knapsack[i+ n][j + m] != 0)) //If the item won't fit in the xDirection, yDirection, or a space "in the item" is already occupied | |
canFit = false; //The item can't fit! | |
//End-of-object check for fit in knapsack | |
if(m + 1 == object.getLength() && n + 1 == object.getWidth() && canFit) //It fits! | |
{ | |
placeObject(i, j, object.getWidth(), object.getLength(), indexInArray); //Place the object | |
return canFit; //Return successful! | |
} | |
else if(m + 1 == object.getLength() && n + 1 == object.getWidth() && !canFit) //It doesn't fit. Increment starting position and try again. | |
canFit = true; | |
} | |
} | |
} | |
} | |
//If the code reaches here, the item wasn't able to be placed. | |
canFit = false; //Not really needed, but the loop exits with canFit = true. Can just return false instead | |
return canFit; | |
} | |
/* Attempts to pack all objects into the knapsack */ | |
public void pack() | |
{ | |
int indexOfObject; | |
int numItemsFit; | |
indexOfObject = 0; | |
numItemsFit = numItems; | |
for(KnapsackObject object : objectArray) | |
{ | |
if(!tryToFit(object, indexOfObject)) //If the item can't be fit using the algorithm, update the numItemsFit | |
numItemsFit--; | |
indexOfObject++; //Combination for & for each. Probably bad practice. | |
} | |
//If all items were able to fit | |
if(numItemsFit == numItems) | |
calculateGoodFitness(); | |
else | |
calculateBadFitness(numItemsFit); | |
} | |
/* Creates an arbitrary *very high* number in relation to Specimen's that managed to fit all objects into the grid. */ | |
public void calculateBadFitness(int numItemsFit) | |
{ | |
//The more items fit, the "more fit" it is, regardless of object size. This is quick and dirty, can be improved | |
fitness = knapsack.length * knapsack[0].length * numItemsFit * 1000; | |
} | |
/* Finds and sets fitness to minimum bounding box for current assignment, only if all objects are placed */ | |
private void calculateGoodFitness() | |
{ | |
int width; | |
int length; | |
int highestWidth; | |
int highestLength; | |
highestWidth = 0; | |
highestLength = 0; | |
width = 0; | |
length = 0; | |
for(int i = 0; i < knapsack.length; i++) | |
{ | |
for(int j = 0; j < knapsack[0].length; j++) | |
{ | |
if(knapsack[i][j] != 0) | |
length = j + 1; | |
} | |
if(length > highestLength) | |
highestLength = length; | |
length = 0; | |
} | |
for(int j = 0; j < knapsack[0].length; j++) | |
{ | |
for(int i = 0; i < knapsack.length; i++) | |
{ | |
if(knapsack[i][j] != 0) | |
width = i + 1; | |
} | |
if(width > highestWidth) | |
highestWidth = width; | |
width = 0; | |
} | |
fitness = highestWidth * highestLength; | |
} | |
//Wrapper for pack() | |
public void determineFitness() | |
{ | |
pack(); | |
} | |
/* Accessors and mutators for private variables */ | |
public int [][] getKnapsack() | |
{ | |
return knapsack; | |
} | |
public ArrayList<KnapsackObject> getObjectArray() | |
{ | |
return objectArray; | |
} | |
public void setObjectArray(ArrayList<KnapsackObject> objectArray) | |
{ | |
this.objectArray = objectArray; | |
} | |
public int getNumItems() | |
{ | |
return numItems; | |
} | |
public int getFitness() | |
{ | |
return fitness; | |
} | |
} |
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