/*
* This file is part of JGAP.
*
* JGAP offers a dual license model containing the LGPL as well as the MPL.
*
* For licensing information please see the file license.txt included with JGAP
* or have a look at the top of class org.jgap.Chromosome which representatively
* includes the JGAP license policy applicable for any file delivered with JGAP.
*/
package examples;
import java.io.*;
import org.jgap.*;
import org.jgap.impl.*;
/**
* See class MinimizingMakeChanged.
* Here a cached fitness function is used instead of an ordinary fitness
* function.
*
* @author Klaus Meffert
* @since 3.2
*/
public class MinimizingMakeChangeCached {
/** String containing the CVS revision. Read out via reflection!*/
private final static String CVS_REVISION = "$Revision: 1.2 $";
/**
* The total number of times we'll let the population evolve.
*/
private static final int MAX_ALLOWED_EVOLUTIONS = 200;
/**
* Executes the genetic algorithm to determine the minimum number of
* coins necessary to make up the given target amount of change. The
* solution will then be written to System.out.
*
* @param a_targetChangeAmount the target amount of change for which this
* method is attempting to produce the minimum number of coins
* @throws Exception
*
* @author Neil Rotstan
* @author Klaus Meffert
* @since 1.0
*/
public static void makeChangeForAmount(int a_targetChangeAmount)
throws Exception {
// Start with a DefaultConfiguration, which comes setup with the
// most common settings.
// -------------------------------------------------------------
Configuration conf = new DefaultConfiguration();
conf.setPreservFittestIndividual(true);
conf.setKeepPopulationSizeConstant(false);
// Set the fitness function we want to use, which is our
// MinimizingMakeChangeFitnessFunction. We construct it with
// the target amount of change passed in to this method.
// ---------------------------------------------------------
FitnessFunction myFunc =
new MinimizingFitnessFunctionCached(a_targetChangeAmount);
conf.setFitnessFunction(myFunc);
conf.resetProperty(Configuration.PROPERTY_FITEVAL_INST);
conf.setFitnessEvaluator(new DeltaFitnessEvaluator());
// Now we need to tell the Configuration object how we want our
// Chromosomes to be setup. We do that by actually creating a
// sample Chromosome and then setting it on the Configuration
// object. As mentioned earlier, we want our Chromosomes to each
// have four genes, one for each of the coin types. We want the
// values (alleles) of those genes to be integers, which represent
// how many coins of that type we have. We therefore use the
// IntegerGene class to represent each of the genes. That class
// also lets us specify a lower and upper bound, which we set
// to sensible values for each coin type.
// --------------------------------------------------------------
Gene[] sampleGenes = new Gene[4];
sampleGenes[0] = new IntegerGene(conf, 0, 3 * 10); // Quarters
sampleGenes[1] = new IntegerGene(conf, 0, 2 * 10); // Dimes
sampleGenes[2] = new IntegerGene(conf, 0, 1 * 10); // Nickels
sampleGenes[3] = new IntegerGene(conf, 0, 4 * 10); // Pennies
IChromosome sampleChromosome = new Chromosome(conf, sampleGenes);
conf.setSampleChromosome(sampleChromosome);
// Finally, we need to tell the Configuration object how many
// Chromosomes we want in our population. The more Chromosomes,
// the larger number of potential solutions (which is good for
// finding the answer), but the longer it will take to evolve
// the population (which could be seen as bad).
// ------------------------------------------------------------
conf.setPopulationSize(80);
// Create random initial population of Chromosomes.
// ------------------------------------------------
Genotype population = Genotype.randomInitialGenotype(conf);
// Evolve the population. Since we don't know what the best answer
// is going to be, we just evolve the max number of times.
// ---------------------------------------------------------------
long startTime = System.currentTimeMillis();
for (int i = 0; i < MAX_ALLOWED_EVOLUTIONS; i++) {
population.evolve();
}
long endTime = System.currentTimeMillis();
System.out.println("Total evolution time: " + (endTime - startTime)
+ " ms");
// Save progress to file. A new run of this example will then be able to
// resume where it stopped before!
// ---------------------------------------------------------------------
// Display the best solution we found.
// -----------------------------------
IChromosome bestSolutionSoFar = population.getFittestChromosome();
System.out.println("The best solution has a fitness value of " +
bestSolutionSoFar.getFitnessValue());
System.out.println("It contained the following: ");
System.out.println("\t" +
MinimizingFitnessFunctionCached.getNumberOfCoinsAtGene(
bestSolutionSoFar, 0) + " quarters.");
System.out.println("\t" +
MinimizingFitnessFunctionCached.getNumberOfCoinsAtGene(
bestSolutionSoFar, 1) + " dimes.");
System.out.println("\t" +
MinimizingFitnessFunctionCached.getNumberOfCoinsAtGene(
bestSolutionSoFar, 2) + " nickels.");
System.out.println("\t" +
MinimizingFitnessFunctionCached.getNumberOfCoinsAtGene(
bestSolutionSoFar, 3) + " pennies.");
System.out.println("For a total of " +
MinimizingFitnessFunctionCached.amountOfChange(
bestSolutionSoFar) + " cents in " +
MinimizingFitnessFunctionCached.getTotalNumberOfCoins(
bestSolutionSoFar) + " coins.");
}
/**
* Main method. A single command-line argument is expected, which is the
* amount of change to create (in other words, 75 would be equal to 75
* cents).
*
* @param args amount of change in cents to create
* @throws Exception
*
* @author Neil Rotstan
* @author Klaus Meffert
* @since 1.0
*/
public static void main(String[] args)
throws Exception {
if (args.length != 1) {
System.out.println("Syntax: MinimizingMakeChange <amount>");
}
else {
int amount = 0;
try {
amount = Integer.parseInt(args[0]);
}
catch (NumberFormatException e) {
System.out.println(
"The <amount> argument must be a valid integer value");
System.exit(1);
}
if (amount < 1 ||
amount >= MinimizingFitnessFunctionCached.MAX_BOUND) {
System.out.println("The <amount> argument must be between 1 and "
+
(MinimizingFitnessFunctionCached.MAX_BOUND - 1)
+ ".");
}
else {
makeChangeForAmount(amount);
}
}
}
}