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Gradients for F6 (Rastrigins)

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This commit is contained in:
Marcel Kronfeld
2009-11-20 10:48:43 +00:00
parent 77395aa7b8
commit 567b7ef1b7
2 changed files with 18 additions and 3 deletions
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19
src/eva2/server/go/problems/F6Problem.java
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@@ -11,7 +11,7 @@ import eva2.tools.math.Jama.Matrix;
* Time: 13:09:36
* To change this template use File | Settings | File Templates.
*/
public class F6Problem extends AbstractProblemDoubleOffset implements InterfaceMultimodalProblem, java.io.Serializable {
public class F6Problem extends AbstractProblemDoubleOffset implements InterfaceMultimodalProblem, InterfaceFirstOrderDerivableProblem, java.io.Serializable {
private boolean doRotation = false;
private double m_A = 10;
@@ -55,7 +55,6 @@ public class F6Problem extends AbstractProblemDoubleOffset implements InterfaceM
* @return The m-dimensional output vector.
*/
public double[] eval(double[] x) {
if (doRotation) {
Matrix resVec = rotation.times(new Matrix(x, x.length));
x = resVec.getColumnPackedCopy();
@@ -68,7 +67,21 @@ public class F6Problem extends AbstractProblemDoubleOffset implements InterfaceM
}
return result;
}
public double[] getFirstOrderGradients(double[] x) {
if (doRotation) {
Matrix resVec = rotation.times(new Matrix(x, x.length));
x = resVec.getColumnPackedCopy();
}
double[] result = new double[x.length];
for (int j=0; j<x.length; j++) {
result[j]=0;
double xj = x[j]-m_XOffSet;
result[j] += 2*xj + this.m_Omega * this.m_A * Math.sin(this.m_Omega*xj);
}
return result;
}
/** This method returns a string describing the optimization problem.
* @return The description.
*/

2
src/eva2/server/go/strategies/GradientDescentAlgorithm.java
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@@ -207,6 +207,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
} // for loop population size
this.m_Problem.evaluate(this.m_Population);
m_Population.incrGeneration();
if (this.recovery) {
for (int i = 0; i < this.m_Population.size(); i++) {
@@ -232,6 +233,7 @@ public class GradientDescentAlgorithm implements InterfaceOptimizer, java.io.Ser
}
}
this.m_Problem.evaluate(this.m_Population);
m_Population.incrGeneration();
}
if (this.globalStepSizeAdaption) {