/*
* 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 org.jgap.impl.job;
import java.util.*;
import org.jgap.*;
import org.jgap.impl.*;
import org.jgap.distr.*;
/**
* Sample implementation of a service that generates jobs, takes them, executes
* them, receives results from finished jobs and merges the results in order to
* start a new round of evolution.
*
* @author Klaus Meffert
* @since 3.2
*/
public class SimpleJobConsumer {
/** String containing the CVS revision. Read out via reflection!*/
private final static String CVS_REVISION = "$Revision: 1.6 $";
private List m_jobs = new Vector();
private List m_results = new Vector();
public void pushJobToGrid(IJob a_job) {
m_jobs.add(a_job);
// Execute the job asynchronously.
// -------------------------------
new Thread(a_job).start();
}
public void waitForAllJobs() {
while (true) {
if (m_jobs.size() < 1) {
break;
}
try {
Thread.sleep(50);
} catch (InterruptedException iex) {
iex.printStackTrace();
break;
}
Iterator it = m_jobs.iterator();
while (it.hasNext()) {
IJob job = (IJob)it.next();
if (job.isFinished()) {
System.out.println("Another job finished!");
m_results.add(job.getResult());
it.remove();
}
}
}
}
public EvolveResult[] getResults() {
int size = m_results.size();
if (size < 1) {
throw new IllegalStateException("No results found!");
}
EvolveResult[] results = new EvolveResult[size];
for(int i=0;i<size;i++) {
results[i] = (EvolveResult)m_results.get(i);
}
return results;
}
public void init()
throws Exception {
Configuration gaConf = new DefaultConfiguration();
gaConf.setPreservFittestIndividual(true);
gaConf.setKeepPopulationSizeConstant(false);
SimpleJobConsumer gridClient = new SimpleJobConsumer();
IChromosome sampleChromosome = new Chromosome(gaConf,
new BooleanGene(gaConf), 16);
gaConf.setSampleChromosome(sampleChromosome);
gaConf.setPopulationSize(20);
gaConf.setFitnessFunction(new MaxFunction());
Genotype genotype = Genotype.randomInitialGenotype(gaConf);
// Run evolution
IPopulationSplitter popSplitter = new SimplePopulationSplitter(3);
for (int i = 0; i < 50; i++) {
// Get jobs, encompass them in a griddable task (only run() supported)
List evolves = genotype.getEvolves(popSplitter);
Iterator it = evolves.iterator();
while (it.hasNext()) {
IEvolveJob evolve = (IEvolveJob) it.next();
gridClient.pushJobToGrid(evolve);
}
// Wait for the jobs.
// ------------------
gridClient.waitForAllJobs();
// Update genotype with all entities, ready for new run
IPopulationMerger popMerger = new FittestPopulationMerger();
genotype.mergeResults(popMerger, gridClient.getResults());
}
// Get best and show info
IChromosome fittest = genotype.getFittestChromosome();
System.out.println("Best solution: " + fittest.toString());
}
public static void main(String[] args) throws Exception {
new SimpleJobConsumer().init();
System.exit(0);
}
}