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/*************************************************************************
*
* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
*
* Copyright 2009 by Sun Microsystems, Inc.
*
* OpenOffice.org - a multi-platform office productivity suite
*
* This file is part of OpenOffice.org.
*
* OpenOffice.org is free software: you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License version 3
* only, as published by the Free Software Foundation.
*
* OpenOffice.org is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License version 3 for more details
* (a copy is included in the LICENSE file that accompanied this code).
*
* You should have received a copy of the GNU Lesser General Public License
* version 3 along with OpenOffice.org. If not, see
* <http://www.openoffice.org/license.html>
* for a copy of the LGPLv3 License.
*
************************************************************************/
package com.sun.star.comp.Calc.NLPSolver;
import java.util.logging.Level;
import java.util.logging.Logger;
import net.adaptivebox.deps.DEPSAgent;
import net.adaptivebox.deps.behavior.DEGTBehavior;
import net.adaptivebox.deps.behavior.PSGTBehavior;
import net.adaptivebox.global.IUpdateCycleEngine;
import net.adaptivebox.knowledge.Library;
import net.adaptivebox.knowledge.SearchPoint;
import com.sun.star.comp.Calc.NLPSolver.dialogs.IEvolutionarySolverStatusDialog;
import com.sun.star.lang.IllegalArgumentException;
import com.sun.star.lang.XSingleComponentFactory;
import com.sun.star.lib.uno.helper.Factory;
import com.sun.star.registry.XRegistryKey;
import com.sun.star.uno.XComponentContext;
public final class DEPSSolverImpl extends BaseEvolutionarySolver
implements com.sun.star.lang.XServiceInfo
{
private static final String m_implementationName = DEPSSolverImpl.class.getName();
private static final String[] m_serviceNames = {
"com.sun.star.sheet.Solver",
"com.sun.star.beans.PropertySet"
};
public DEPSSolverImpl( XComponentContext context )
{
super(context, "DEPS Evolutionary Algorithm");
registerProperty(m_agentSwitchRate);
registerProperty(m_factor);
registerProperty(m_CR);
registerProperty(m_c1);
registerProperty(m_c2);
registerProperty(m_weight);
registerProperty(m_CL);
}
public static XSingleComponentFactory __getComponentFactory( String sImplementationName ) {
XSingleComponentFactory xFactory = null;
if ( sImplementationName.equals( m_implementationName ) )
xFactory = Factory.createComponentFactory(DEPSSolverImpl.class, m_serviceNames);
return xFactory;
}
public static boolean __writeRegistryServiceInfo( XRegistryKey xRegistryKey ) {
return Factory.writeRegistryServiceInfo(m_implementationName,
m_serviceNames,
xRegistryKey);
}
// com.sun.star.lang.XServiceInfo:
public String getImplementationName() {
return m_implementationName;
}
public boolean supportsService( String sService ) {
int len = m_serviceNames.length;
for( int i=0; i < len; i++) {
if (sService.equals(m_serviceNames[i]))
return true;
}
return false;
}
public String[] getSupportedServiceNames() {
return m_serviceNames;
}
// com.sun.star.sheet.XSolver:
private DEPSAgent[] m_agents;
private PropertyInfo<Double> m_agentSwitchRate = new PropertyInfo<Double>("AgentSwitchRate", 0.5, "Agent Switch Rate (DE Probability)");
// --DE
private PropertyInfo<Double> m_factor = new PropertyInfo<Double>("DEFactor", 0.5, "DE: Scaling Factor (0-1.2)");
private PropertyInfo<Double> m_CR = new PropertyInfo<Double>("DECR", 0.9, "DE: Crossover Probability (0-1)");
// --PS
private PropertyInfo<Double> m_c1 = new PropertyInfo<Double>("PSC1", 1.494, "PS: Cognitive Constant");
private PropertyInfo<Double> m_c2 = new PropertyInfo<Double>("PSC2", 1.494, "PS: Social Constant");
private PropertyInfo<Double> m_weight = new PropertyInfo<Double>("PSWeight", 0.729, "PS: Constriction Coefficient");
private PropertyInfo<Double> m_CL = new PropertyInfo<Double>("PSCL", 0.0, "PS: Mutation Probability (0-0.005)");
public void solve() {
try {
m_librarySize.setValue(m_swarmSize.getValue()); //DEPS' library is as large as the swarm
} catch (IllegalArgumentException ex) {
Logger.getLogger(DEPSSolverImpl.class.getName()).log(Level.SEVERE, null, ex);
}
initializeSolve();
//Init:
m_agents = new DEPSAgent[m_swarmSize.getValue()];
for (int i = 0; i < m_swarmSize.getValue(); i++) {
m_agents[i] = new DEPSAgent();
m_agents[i].setProblemEncoder(m_problemEncoder);
m_agents[i].setPbest(m_library.getSelectedPoint(i));
DEGTBehavior deGTBehavior = new DEGTBehavior();
deGTBehavior.FACTOR = m_factor.getValue();
deGTBehavior.CR = m_CR.getValue();
PSGTBehavior psGTBehavior = new PSGTBehavior();
psGTBehavior.c1 = m_c1.getValue();
psGTBehavior.c2 = m_c2.getValue();
psGTBehavior.CL = m_CL.getValue();
psGTBehavior.weight = m_weight.getValue();
m_agents[i].switchP = m_agentSwitchRate.getValue();
m_agents[i].setGTBehavior(deGTBehavior);
m_agents[i].setGTBehavior(psGTBehavior);
m_agents[i].setSpecComparator(m_specCompareEngine);
m_agents[i].setLibrary(m_library);
}
//Learn:
m_solverStatusDialog.setVisible(true);
m_solverStatusDialog.setMaxIterations(m_learningCycles.getValue());
m_solverStatusDialog.setMaxStagnation(m_required.getValue());
int learningCycle = 1;
long runtime = 0;
do {
long startTime = System.nanoTime();
if (learningCycle >= m_learningCycles.getValue())
learningCycle = 1;
if (m_solverStatusDialog.getUserState() == IEvolutionarySolverStatusDialog.CONTINUE)
lockDocument();
m_toleratedCount = 0;
m_toleratedMin = -1.0 * m_tolerance.getValue();
m_toleratedMax = m_tolerance.getValue();
for (; learningCycle <= m_learningCycles.getValue() &&
m_toleratedCount < m_required.getValue() &&
m_solverStatusDialog.getUserState() != IEvolutionarySolverStatusDialog.CANCEL; learningCycle++) {
m_library.refreshGbest(m_specCompareEngine);
for (int i = 0; i < m_swarmSize.getValue(); i++)
m_agents[i].generatePoint();
for (int i = 0; i < m_swarmSize.getValue(); i++)
m_agents[i].learn();
for (int i = 0; i < m_swarmSize.getValue(); i++) {
SearchPoint agentPoint = m_agents[i].getMGState();
boolean inRange = (agentPoint.getObjectiveValue() >= m_toleratedMin && agentPoint.getObjectiveValue() <= m_toleratedMax);
if (Library.replace(m_envCompareEngine, agentPoint, m_totalBestPoint)) {
m_solverStatusDialog.setBestSolution(m_totalBestPoint.getObjectiveValue(), m_totalBestPoint.isFeasible());
if (!inRange) {
m_toleratedMin = agentPoint.getObjectiveValue() - m_tolerance.getValue();
m_toleratedMax = agentPoint.getObjectiveValue() + m_tolerance.getValue();
m_toleratedCount = 0;
}
}
}
if (m_specCompareEngine instanceof IUpdateCycleEngine)
((IUpdateCycleEngine)m_specCompareEngine).updateCycle(learningCycle);
m_solverStatusDialog.setIteration(learningCycle);
m_solverStatusDialog.setStagnation(m_toleratedCount);
m_solverStatusDialog.setRuntime(runtime + (System.nanoTime() - startTime));
m_xReschedule.reschedule();
}
applySolution(); //show the current solution
unlockDocument(); //allow the solution to be displayed
runtime += (System.nanoTime() - startTime);
m_solverStatusDialog.setRuntime(runtime);
} while (m_solverStatusDialog.waitForUser() == IEvolutionarySolverStatusDialog.CONTINUE);
lockDocument();
finalizeSolve();
}
}
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