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Re: [cilib-devel] [PATCH] Constriction PSO
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From: Gary P. <gpa...@gm...> - 2009-07-03 06:30:24
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Patch looks good. This is something that we have needed to add for a while
now.
The test cases are a little complex though. Especially the
testUpdateAndConstraintAssertion(). The tests should ideally be testing one
thing per test.
In the first part of the test, the following is executed:
MersenneTwister twister = new MersenneTwister();
FunctionMinimisationProblem problem = new
FunctionMinimisationProblem();
problem.setFunction(new Spherical());
StandardParticle nBest = new StandardParticle();
StandardParticle particle = new StandardParticle();
particle.initialise(problem);
nBest.initialise(problem);
particle.getVelocity().randomize(twister);
particle.setNeighbourhoodBest(nBest);
ConstrictionVelocityUpdate constrictionVelocityUpdate = new
ConstrictionVelocityUpdate();
boolean assertionExceptionOccured = false;
try {
constrictionVelocityUpdate.updateVelocity(particle);
}
catch(UnsupportedOperationException ex) {
assertionExceptionOccured = true;
}
I understand the need to have c_1 + c_2 < 4, but is there a reason why the are
defaultly set to 3.0? Also, the execption thrown in the check within the
ConstrictionVelocityUpdate states that the values should be "greater or equal
to 4". I assume that was a typo? Or is the logic incorrect?
The last part of that test tests that an exception is expected. We should
create a new test method for that with a signature similar to:
@Test(expected=UnsupportedOperationException.class)
public void illegalVelocityUpdate() {
....
Or something similar :P I also want to see if we can't mock some of the
objects in the test to make the unit test more isolated.
Regards,
Gary
On Thursday 02 July 2009 14:46:24 Andrich wrote:
> Added a velocity update strategy for a Constriction PSO as well as its unit
> test. ---
> .../ConstrictionVelocityUpdate.java | 243
> ++++++++++++++++++++ .../ConstrictionVelocityUpdateTest.java |
> 144 ++++++++++++ xml/constrictionPSO.xml | 57
> +++++
> 3 files changed, 444 insertions(+), 0 deletions(-)
> create mode 100644
> src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constricti
>onVelocityUpdate.java create mode 100644
> src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constricti
>onVelocityUpdateTest.java create mode 100644 xml/constrictionPSO.xml
>
> diff --git
> a/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdate.java
> b/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdate.java new file mode 100644
> index 0000000..41d955b
> --- /dev/null
> +++
> b/src/main/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdate.java @@ -0,0 +1,243 @@
> +/**
> + * Copyright (C) 2003 - 2009
> + * Computational Intelligence Research Group (CIRG@UP)
> + * Department of Computer Science
> + * University of Pretoria
> + * South Africa
> + *
> + * This program is free software; you can redistribute it and/or modify
> + * it under the terms of the GNU General Public License as published by
> + * the Free Software Foundation; either version 2 of the License, or
> + * (at your option) any later version.
> + *
> + * This program 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 General Public License for more details.
> + *
> + * You should have received a copy of the GNU General Public License
> + * along with this program; if not, write to the Free Software
> + * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
> USA + */
> +package net.sourceforge.cilib.pso.velocityupdatestrategies;
> +
> +import net.sourceforge.cilib.controlparameter.ConstantControlParameter;
> +import net.sourceforge.cilib.controlparameter.ControlParameter;
> +import net.sourceforge.cilib.controlparameter.RandomizingControlParameter;
> +import net.sourceforge.cilib.entity.Particle;
> +import net.sourceforge.cilib.type.types.container.Vector;
> +
> +/**
> + * A velocity update strategy that utilizes the constriction coefficient
> as + * developed by Clerc. References:
> + * <ul>
> + * <li>
> + * Inproceedings (Clerc1999)
> + * Clerc, M.
> + * The swarm and the queen: towards a deterministic and adaptive particle
> swarm + * optimization
> + * Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999
> Congress on, + * 1999, 3, -1957 Vol. 3
> + * </li>
> + * <li>
> + * Article (Clerc2002)
> + * Clerc, M. & Kennedy, J.
> + * The particle swarm - explosion, stability, and convergence in a
> + * multidimensional complex space Evolutionary Computation,
> + * IEEE Transactions on, 2002, 6, 58-73
> + * </li>
> + * </ul>
> + *
> + * Note, this strategy does not the inertia control parameter.
> + * Certain constraints are imposed on the other control parameters in
> order to + * calculate the constriction coefficient, namely:
> + * $c1r1 + c2r2 \leq 4$ , and
> + * $\kappa \in [0, 1]$
> + *
> + * @author andrich
> + */
> +public class ConstrictionVelocityUpdate implements VelocityUpdateStrategy
> { +
> + protected ControlParameter socialAcceleration;
> + protected ControlParameter cognitiveAcceleration;
> + protected ControlParameter vMax;
> + protected ControlParameter kappa;
> +
> + /**
> + * Default constructor. The values given to the control parameters
> attempt to + * adhere to the constraints of calculating the
> constriction constant, but do not + * necessarily represent good
> values.
> + */
> + public ConstrictionVelocityUpdate() {
> + socialAcceleration = new RandomizingControlParameter();
> + cognitiveAcceleration = new RandomizingControlParameter();
> + vMax = new ConstantControlParameter();
> + kappa = new ConstantControlParameter();
> +
> + socialAcceleration.setParameter(3.0);
> + cognitiveAcceleration.setParameter(3.0);
> + vMax.setParameter(Double.MAX_VALUE);
> + kappa.setParameter(0.1);
> + }
> +
> + /**
> + * Copy constructor.
> + * @param orig the ConstrictionVelocityUpdate to copy.
> + */
> + public ConstrictionVelocityUpdate(ConstrictionVelocityUpdate orig) {
> + this.socialAcceleration = new
> RandomizingControlParameter((RandomizingControlParameter)
> orig.socialAcceleration); + this.cognitiveAcceleration = new
> RandomizingControlParameter((RandomizingControlParameter)
> orig.cognitiveAcceleration); + this.vMax = new
> ConstantControlParameter((ConstantControlParameter) orig.vMax); +
> this.kappa = new ConstantControlParameter((ConstantControlParameter)
> orig.kappa); + }
> +
> + /**
> + * {@inheritDoc }
> + */
> + @Override
> + public VelocityUpdateStrategy getClone() {
> + return new ConstrictionVelocityUpdate(this);
> + }
> +
> + /**
> + * {@inheritDoc }
> + */
> + @Override
> + public void updateVelocity(Particle particle) {
> + assertAccelerationConstraints();
> +
> + Vector velocity = (Vector) particle.getVelocity();
> + Vector position = (Vector) particle.getPosition();
> + Vector bestPosition = (Vector) particle.getBestPosition();
> + Vector nBestPosition = (Vector)
> particle.getNeighbourhoodBest().getBestPosition(); +
> +
> + for (int i = 0; i < particle.getDimension(); ++i) {
> + // calculate the constriction coefficient
> + double c1 = cognitiveAcceleration.getParameter();
> + double c2 = socialAcceleration.getParameter();
> + // c1r1 + c2r2 has to be greater or equal to 4
> + while ((c1 + c2) < 4) {
> + c1 = cognitiveAcceleration.getParameter();
> + c2 = socialAcceleration.getParameter();
> + }
> + double phi = c1 + c2;
> + double constrictionCoefficient = (2 * kappa.getParameter()) /
> + Math.abs(2 - phi - Math.sqrt(phi * (phi - 4.0)));
> +
> + double value = velocity.getReal(i) +
> + (bestPosition.getReal(i) - position.getReal(i)) * c1 +
> + (nBestPosition.getReal(i) - position.getReal(i)) * c2;
> + value = constrictionCoefficient * value;
> + velocity.setReal(i, value);
> +
> + clamp(velocity, i);
> + }
> + }
> +
> + /**
> + * Clamp to maximum velocity.
> + * @param velocity The {@link Vector} to be clamped.
> + * @param i The dimension index to be clamped
> + */
> + protected void clamp(Vector velocity, int i) {
> + // if vMax is not set (or set as max), it is unnecessary to clamp
> + if (Double.compare(vMax.getParameter(), Double.MAX_VALUE) == 0) {
> + return;
> + }
> + if (velocity.getReal(i) < -vMax.getParameter()) {
> + velocity.setReal(i, -vMax.getParameter());
> + } else if (velocity.getReal(i) > vMax.getParameter()) {
> + velocity.setReal(i, vMax.getParameter());
> + }
> + }
> +
> + /**
> + * {@inheritDoc }
> + */
> + @Override
> + public void updateControlParameters(Particle particle) {
> + this.kappa.updateParameter();
> + this.cognitiveAcceleration.updateParameter();
> + this.socialAcceleration.updateParameter();
> + this.vMax.updateParameter();
> + }
> +
> + /**
> + * Ensure that values of c1 and c2 make it possible to calculate the
> + * constriction coefficient.
> + */
> + private void assertAccelerationConstraints() {
> + double c1 = ((RandomizingControlParameter)
> cognitiveAcceleration).getControlParameter().getParameter(); +
> double c2 = ((RandomizingControlParameter)
> socialAcceleration).getControlParameter().getParameter(); + if (c1 +
> c2 < 4) {
> + throw new UnsupportedOperationException("Parameter constraint
> violation: " + + "The sum of the Cognitive (" + c1 + ")
> and Social (" + c2 + ") acceleration parameters " + +
> "has to be greater than or equal to 4.");
> + }
> + }
> +
> + /**
> + * Get the coginitive acceleration parameter.
> + * @return the cognitive acceleration {@link ControlParameter control
> parameter }. + */
> + public ControlParameter getCognitiveAcceleration() {
> + return cognitiveAcceleration;
> + }
> +
> + /**
> + * Set the coginitive acceleration parameter.
> + * @param cognitiveAcceleration the new cognitive acceleration {@link
> ControlParameter control parameter }. + */
> + public void setCognitiveAcceleration(ControlParameter
> cognitiveAcceleration) { + this.cognitiveAcceleration =
> cognitiveAcceleration;
> + }
> +
> + /**
> + * Get the Kappa control parameter.
> + * @return the kappa {@link ControlParameter control parameter }.
> + */
> + public ControlParameter getKappa() {
> + return kappa;
> + }
> +
> + /**
> + * Set the Kappa control parameter.
> + * @param kappa the new kappa {@link ControlParameter control
> parameter }. + */
> + public void setKappa(ControlParameter kappa) {
> + this.kappa = kappa;
> + }
> +
> + /**
> + * Get the social acceleration parameter.
> + * @return the social acceleration {@link ControlParameter control
> parameter }. + */
> + public ControlParameter getSocialAcceleration() {
> + return socialAcceleration;
> + }
> +
> + /**
> + * Set the social acceleration parameter.
> + * @param socialAcceleration the new social accerelation {@link
> ControlParameter control parameter }. + */
> + public void setSocialAcceleration(ControlParameter socialAcceleration)
> { + this.socialAcceleration = socialAcceleration;
> + }
> +
> + /**
> + * Get the maximum velocity parameter.
> + * @return the maximum velocity {@link ControlParameter control
> parameter }. + */
> + public ControlParameter getVMax() {
> + return vMax;
> + }
> +
> + /**
> + * Set the maximum velocity parameter.
> + * @param vMax the new maximum velocity {@link ControlParameter
> control parameter }. + */
> + public void setVMax(ControlParameter vMax) {
> + this.vMax = vMax;
> + }
> +}
> diff --git
> a/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdateTest.java
> b/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdateTest.java new file mode 100644
> index 0000000..189cca9
> --- /dev/null
> +++
> b/src/test/java/net/sourceforge/cilib/pso/velocityupdatestrategies/Constric
>tionVelocityUpdateTest.java @@ -0,0 +1,144 @@
> +/**
> + * Copyright (C) 2003 - 2009
> + * Computational Intelligence Research Group (CIRG@UP)
> + * Department of Computer Science
> + * University of Pretoria
> + * South Africa
> + *
> + * This program is free software; you can redistribute it and/or modify
> + * it under the terms of the GNU General Public License as published by
> + * the Free Software Foundation; either version 2 of the License, or
> + * (at your option) any later version.
> + *
> + * This program 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 General Public License for more details.
> + *
> + * You should have received a copy of the GNU General Public License
> + * along with this program; if not, write to the Free Software
> + * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
> USA + */
> +package net.sourceforge.cilib.pso.velocityupdatestrategies;
> +
> +import net.sourceforge.cilib.controlparameter.ConstantControlParameter;
> +import net.sourceforge.cilib.controlparameter.RandomizingControlParameter;
> +import net.sourceforge.cilib.functions.continuous.Spherical;
> +import net.sourceforge.cilib.math.Maths;
> +import net.sourceforge.cilib.math.random.generator.MersenneTwister;
> +import net.sourceforge.cilib.problem.FunctionMinimisationProblem;
> +import net.sourceforge.cilib.pso.particle.StandardParticle;
> +import net.sourceforge.cilib.type.types.Numeric;
> +import net.sourceforge.cilib.type.types.container.Vector;
> +import org.junit.Assert;
> +import org.junit.Test;
> +
> +/**
> + * Unit test for the constriction velocity update.
> + * @author andrich
> + */
> +public class ConstrictionVelocityUpdateTest {
> +
> + /**
> + * Test cloning and implicetly the copy constructor.
> + */
> + @Test
> + public void testClone() {
> + ConstrictionVelocityUpdate original = new
> ConstrictionVelocityUpdate(); + ConstrictionVelocityUpdate copy =
> (ConstrictionVelocityUpdate) original.getClone(); +
> + Assert.assertEquals(original.getKappa().getParameter(),
> copy.getKappa().getParameter(), Maths.EPSILON); +
> Assert.assertEquals(original.getVMax().getParameter(),
> copy.getVMax().getParameter(), Maths.EPSILON); +
> Assert.assertEquals(((RandomizingControlParameter)original.cognitiveAcceler
>ation).getControlParameter().getParameter(), +
> ((RandomizingControlParameter)copy.cognitiveAcceleration).getControlParamet
>er().getParameter(), Maths.EPSILON); +
> Assert.assertEquals(((RandomizingControlParameter)original.socialAccelerati
>on).getControlParameter().getParameter(), +
> ((RandomizingControlParameter)copy.socialAcceleration).getControlParameter(
>).getParameter(), Maths.EPSILON); +
> + copy.setKappa(new ConstantControlParameter(0.7));
> + copy.setVMax(new ConstantControlParameter(0.7));
> + RandomizingControlParameter randomizingControlParameter = new
> RandomizingControlParameter(); +
> randomizingControlParameter.setParameter(4.0);
> + copy.setSocialAcceleration(new
> RandomizingControlParameter(randomizingControlParameter.getClone())); +
> copy.setCognitiveAcceleration(new
> RandomizingControlParameter(randomizingControlParameter.getClone())); +
> +
> Assert.assertFalse(Double.compare(original.getKappa().getParameter(),
> copy.getKappa().getParameter()) == 0); +
> Assert.assertFalse(Double.compare(original.getVMax().getParameter(),
> copy.getVMax().getParameter()) == 0); +
> Assert.assertFalse(Double.compare(((RandomizingControlParameter)original.co
>gnitiveAcceleration).getControlParameter().getParameter(), +
> ((RandomizingControlParameter)copy.cognitiveAcceleration).getControlParamet
>er().getParameter()) == 0); +
> Assert.assertFalse(Double.compare(((RandomizingControlParameter)original.so
>cialAcceleration).getControlParameter().getParameter(), +
> ((RandomizingControlParameter)copy.socialAcceleration).getControlParameter(
>).getParameter()) == 0); + }
> +
> + /**
> + * Test the velocity update as well as the constraint assertion.
> + */
> + @Test
> + public void testUpdateAndConstraintAssertion() {
> + MersenneTwister twister = new MersenneTwister();
> + FunctionMinimisationProblem problem = new
> FunctionMinimisationProblem(); + problem.setFunction(new
> Spherical());
> +
> + StandardParticle nBest = new StandardParticle();
> + StandardParticle particle = new StandardParticle();
> + particle.initialise(problem);
> + nBest.initialise(problem);
> + ((Vector)particle.getVelocity()).randomize(twister);
> + particle.setNeighbourhoodBest(nBest);
> +
> + ConstrictionVelocityUpdate constrictionVelocityUpdate = new
> ConstrictionVelocityUpdate(); +
> + boolean assertionExceptionOccured = false;
> + try {
> + constrictionVelocityUpdate.updateVelocity(particle);
> + }
> + catch(UnsupportedOperationException ex) {
> + assertionExceptionOccured = true;
> + }
> +
> + Assert.assertFalse(assertionExceptionOccured);
> +
> + RandomizingControlParameter randomizingControlParameter = new
> RandomizingControlParameter(); +
> randomizingControlParameter.setParameter(1.0);
> + constrictionVelocityUpdate.setSocialAcceleration(new
> RandomizingControlParameter(randomizingControlParameter.getClone())); +
> constrictionVelocityUpdate.setCognitiveAcceleration(new
> RandomizingControlParameter(randomizingControlParameter.getClone())); +
> + assertionExceptionOccured = false;
> + try {
> + constrictionVelocityUpdate.updateVelocity(particle);
> + }
> + catch(UnsupportedOperationException ex) {
> + assertionExceptionOccured = true;
> + }
> +
> + Assert.assertTrue(assertionExceptionOccured);
> +
> + }
> +
> + /**
> + * Test velocity clamping.
> + */
> + @Test
> + public void testClamping() {
> + MersenneTwister twister = new MersenneTwister();
> + FunctionMinimisationProblem problem = new
> FunctionMinimisationProblem(); + problem.setFunction(new
> Spherical());
> +
> + StandardParticle nBest = new StandardParticle();
> + StandardParticle particle = new StandardParticle();
> + particle.initialise(problem);
> + nBest.initialise(problem);
> + ((Vector)particle.getVelocity()).randomize(twister);
> + particle.setNeighbourhoodBest(nBest);
> +
> + ConstrictionVelocityUpdate constrictionVelocityUpdate = new
> ConstrictionVelocityUpdate(); +
> constrictionVelocityUpdate.setVMax(new ConstantControlParameter(0.5)); +
> constrictionVelocityUpdate.updateVelocity(particle);
> + Vector velocity = particle.getVelocity();
> + for (Numeric number : velocity) {
> + Assert.assertTrue(Double.compare(number.getReal(), 0.5) <= 0);
> + Assert.assertTrue(Double.compare(number.getReal(), -0.5) >=
> 0); + }
> +
> + }
> +
> +}
> diff --git a/xml/constrictionPSO.xml b/xml/constrictionPSO.xml
> new file mode 100644
> index 0000000..77c3eb4
> --- /dev/null
> +++ b/xml/constrictionPSO.xml
> @@ -0,0 +1,57 @@
> +<?xml version="1.0"?>
> +<!DOCTYPE simulator [
> +<!ATTLIST algorithm id ID #IMPLIED>
> +<!ATTLIST problem id ID #IMPLIED>
> +<!ATTLIST measurements id ID #IMPLIED>
> +]>
> +<simulator>
> + <algorithms>
> + <algorithm id="constrictionPSO" class="pso.PSO">
> + <initialisationStrategy
> class="algorithm.initialisation.ClonedPopulationInitialisationStrategy"> +
> <entityType class="pso.particle.StandardParticle"> +
> <velocityUpdateStrategy
> class="pso.velocityupdatestrategies.ConstrictionVelocityUpdate"> +
> <kappa class="controlparameter.ConstantControlParameter"
> parameter="0.1" /> + <socialAcceleration
> class="controlparameter.RandomizingControlParameter" parameter="3.0" /> +
> <cognitiveAcceleration
> class="controlparameter.RandomizingControlParameter" parameter="3.0" /> +
> <!--vMax
> class="controlparameter.ConstantControlParameter" parameter="0.1" /--> +
> </velocityUpdateStrategy>
> + </entityType>
> + </initialisationStrategy>
> + <topology class="entity.topologies.GBestTopology"/>
> + <addStoppingCondition
> class="stoppingcondition.MaximumIterations" maximumIterations="1000"/> +
> </algorithm>
> + </algorithms>
> +
> + <problems>
> + <problem id="spherical"
> class="problem.FunctionMinimisationProblem"> + <function
> class="functions.continuous.Spherical"/>
> + </problem>
> + <problem id="rosenbrock"
> class="problem.FunctionMinimisationProblem"> + <function
> class="functions.continuous.Rosenbrock"/>
> + </problem>
> + <problem id="rastrigin"
> class="problem.FunctionMinimisationProblem"> + <function
> class="functions.continuous.unconstrained.Rastrigin"/> + </problem>
> + </problems>
> +
> + <measurements id="fitness" class="simulator.MeasurementSuite"
> resolution="10" samples="1"> + <addMeasurement
> class="measurement.single.Fitness"/>
> + </measurements>
> + <simulations>
> + <simulation>
> + <algorithm idref="constrictionPSO"/>
> + <problem idref="spherical"/>
> + <measurements idref="fitness"
> file="data/constrictionpso_spherical.txt"/> + </simulation>
> + <simulation>
> + <algorithm idref="constrictionPSO"/>
> + <problem idref="rosenbrock"/>
> + <measurements idref="fitness"
> file="data/constrictionpso_rosenbrock.txt"/> + </simulation>
> + <simulation>
> + <algorithm idref="constrictionPSO"/>
> + <problem idref="rastrigin"/>
> + <measurements idref="fitness"
> file="data/constrictionpso_rastrigin.txt"/> + </simulation>
> + </simulations>
> +</simulator>
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