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Corrected offsets for F*Problems

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This commit is contained in:
Marcel Kronfeld
2009-10-14 15:42:01 +00:00
parent f9213d167f
commit e173da91e1
15 changed files with 48 additions and 51 deletions
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4
src/eva2/gui/GenericObjectEditor.java
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@@ -297,7 +297,7 @@ public class GenericObjectEditor implements PropertyEditor {
return;
}
Vector<String> v;
Vector<String> v=null;
if (Proxy.isProxyClass(m_ClassType)) {
if (TRACE) System.out.println("PROXY! original was " + ((RMIProxyLocal)Proxy.getInvocationHandler(((Proxy)m_Object))).getOriginalClass().getName());
v = new Vector<String>(getClassesFromProperties(((RMIProxyLocal)Proxy.getInvocationHandler(((Proxy)m_Object))).getOriginalClass().getName()));
@@ -305,7 +305,7 @@ public class GenericObjectEditor implements PropertyEditor {
v = new Vector<String>(getClassesFromProperties(m_ClassType.getName()));
}
v = new Vector<String>(getClassesFromProperties(m_ClassType.getName()));
// v = new Vector<String>(getClassesFromProperties(m_ClassType.getName()));
try {
if (v.size() > 0)
setObject((Object)Class.forName((String)v.get(0)).newInstance());

11
src/eva2/server/go/problems/AbstractOptimizationProblem.java
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@@ -1,7 +1,6 @@
package eva2.server.go.problems;
import java.awt.BorderLayout;
import java.util.ArrayList;
import java.util.Vector;
import java.io.Serializable;
@@ -51,11 +50,13 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
}
public void run() {
// System.out.println("Running ET " + this);
// long time=System.nanoTime();
prob.evaluate(ind);
resultrep.add(ind);
pop.incrFunctionCalls();
// long duration=System.nanoTime()-time;
// System.out.println("Finished ET" + this + ", time was " + duration);
}
}
@@ -102,8 +103,8 @@ public abstract class AbstractOptimizationProblem implements InterfaceOptimizati
evaluatePopulationStart(population);
if (this.parallelthreads > 1) {
Vector<AbstractEAIndividual> queue = new Vector<AbstractEAIndividual>();
Vector<AbstractEAIndividual> finished = new Vector<AbstractEAIndividual>();
Vector<AbstractEAIndividual> queue = new Vector<AbstractEAIndividual>(population.size());
Vector<AbstractEAIndividual> finished = new Vector<AbstractEAIndividual>(population.size());
queue.addAll(population);
while (finished.size() < population.size()) {

5
src/eva2/server/go/problems/F10Problem.java
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@@ -39,9 +39,10 @@ public class F10Problem extends F1Problem implements InterfaceMultimodalProblem,
public double[] eval(double[] x) {
double[] result = new double[1];
double c1 = this.calculateC(1);
result[0] = 0.;
result[0] = m_YOffSet;
for (int i = 0; i < x.length-1; i++) {
result[0] += ((this.calculateC(x[i]))/(c1 * Math.pow(Math.abs(x[i]),2-this.m_D))) + Math.pow(x[i], 2) -1;
double xi = x[i]-m_XOffSet;
result[0] += ((this.calculateC(xi))/(c1 * Math.pow(Math.abs(xi),2-this.m_D))) + Math.pow(xi, 2) -1;
}
return result;
}

8
src/eva2/server/go/problems/F11Problem.java
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@@ -41,12 +41,12 @@ public class F11Problem extends F1Problem implements InterfaceMultimodalProblem,
public double[] eval(double[] x) {
double[] result = new double[1];
double tmpProd = 1;
result[0] = 0;
for (int i = 0; i < x.length; i++) {
result[0] += Math.pow(x[i], 2);
tmpProd *= Math.cos((x[i])/Math.sqrt(i+1));
double xi = x[i]-m_XOffSet;
result[0] += Math.pow(xi, 2);
tmpProd *= Math.cos((xi)/Math.sqrt(i+1));
}
result[0] = ((result[0]/this.m_D) - tmpProd + 1);
result[0] = ((result[0]/this.m_D) - tmpProd + 1)+m_YOffSet;
return result;
}

6
src/eva2/server/go/problems/F12Problem.java
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@@ -36,11 +36,11 @@ public class F12Problem extends F1Problem implements java.io.Serializable {
public double[] eval(double[] x) {
double[] result = new double[1];
double tmp = -5;
result[0] = 0;
for (int i = 1; i < x.length-1; i++) {
tmp += Math.pow(x[i], 2);
tmp += Math.pow(x[i]-m_XOffSet, 2);
}
result[0] = (Math.exp(-5*x[0]*x[0])+2*Math.exp(-5*Math.pow(1-x[0], 2)))*Math.exp(tmp);
double x0 = x[0]-m_XOffSet;
result[0] = m_YOffSet+(Math.exp(-5*x0*x0)+2*Math.exp(-5*Math.pow(1-x0, 2)))*Math.exp(tmp);
return result;
}

5
src/eva2/server/go/problems/F13Problem.java
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@@ -42,10 +42,11 @@ public class F13Problem extends F1Problem implements InterfaceMultimodalProblem
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
for (int i=0; i<x.length; i++) {
result[0] -= x[i]*Math.sin(Math.sqrt(Math.abs(x[i])));
double xi = x[i]-m_XOffSet;
result[0] -= xi*Math.sin(Math.sqrt(Math.abs(xi)));
}
result[0] += (418.9829 * m_ProblemDimension);
return result;

10
src/eva2/server/go/problems/F14Problem.java
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@@ -30,14 +30,10 @@ public class F14Problem extends F1Problem implements InterfaceMultimodalProblem,
return (Object) new F14Problem(this);
}
/** Ths method allows you to evaluate a double[] to determine the fitness
* @param x The n-dimensional input vector
* @return The m-dimensional output vector.
*/
public double[] eval(double[] x) {
double[] result = new double[1];
double x0 = x[0]-rotationDX;
double x1 = x[1]-rotationDX;
double x0 = x[0]-rotationDX-m_XOffSet;
double x1 = x[1]-rotationDX-m_XOffSet;
if (rotation != 0.) {
double cosw = Math.cos(rotation);
double sinw = Math.sin(rotation);
@@ -47,7 +43,7 @@ public class F14Problem extends F1Problem implements InterfaceMultimodalProblem,
x0=tmpx0;
}
//matlab: 40 + (- exp(cos(5*X)+cos(3*Y)) .* exp(-X.^2) .* (-.05*Y.^2+5));
result[0] = 36.9452804947;//36.945280494653247;
result[0] = m_YOffSet+36.9452804947;//36.945280494653247;
result[0] += (-Math.exp(Math.cos(3*x0)+Math.cos(6*x1)) * Math.exp(-x0*x0/10) * (-.05*x1*x1+5));
return result;

9
src/eva2/server/go/problems/F2Problem.java
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@@ -31,11 +31,14 @@ public class F2Problem extends F1Problem implements InterfaceMultimodalProblem,
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
double xi, xii;
for (int i = 0; i < x.length-1; i++) {
result[0] += (100*(x[i+1]-x[i]*x[i])*(x[i+1]-x[i]*x[i])+(x[i]-1)*(x[i]-1));
xi=x[i]-m_XOffSet;
xii=x[i+1]-m_XOffSet;
result[0] += (100*(xii-xi*xi)*(xii-xi*xi)+(xi-1)*(xi-1));
}
if (result[0]<=0) result[0]=Math.sqrt(Double.MIN_VALUE); // guard for plots in log scale
if (m_YOffSet==0 && (result[0]<=0)) result[0]=Math.sqrt(Double.MIN_VALUE); // guard for plots in log scale
return result;
}

4
src/eva2/server/go/problems/F3Problem.java
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@@ -32,9 +32,9 @@ public class F3Problem extends F1Problem implements java.io.Serializable {
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 6*x.length;
result[0] = m_YOffSet+6*x.length;
for (int i = 0; i < x.length-1; i++) {
result[0] += Math.floor(x[i]);
result[0] += Math.floor(x[i]- this.m_XOffSet);
}
return result;
}

4
src/eva2/server/go/problems/F4Problem.java
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@@ -36,9 +36,9 @@ public class F4Problem extends F1Problem implements java.io.Serializable {
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
for (int i = 0; i < x.length-1; i++) {
result[0] += (i+1)*Math.pow(x[i], 4);
result[0] += (i+1)*Math.pow((x[i]-m_XOffSet), 4);
}
return result;
}

4
src/eva2/server/go/problems/F5Problem.java
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@@ -37,11 +37,11 @@ public class F5Problem extends F1Problem implements java.io.Serializable {
public double[] eval(double[] x) {
double[] result = new double[1];
double tmp;
result[0] = 0;
result[0] = m_YOffSet;
for (int i = 0; i < x.length-1; i++) {
tmp = 0;
for (int j = 0; j <= i; j++) {
tmp += x[j];
tmp += x[j]-m_XOffSet;
}
result[0] += Math.pow(tmp, 2);
}

5
src/eva2/server/go/problems/F6Problem.java
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@@ -58,9 +58,10 @@ public class F6Problem extends F1Problem implements InterfaceMultimodalProblem,
x = resVec.getColumnPackedCopy();
}
double[] result = new double[1];
result[0] = x.length * this.m_A;
result[0] = x.length * this.m_A + m_YOffSet;
for (int i = 0; i < x.length; i++) {
result[0] += Math.pow(x[i], 2) - this.m_A * Math.cos(this.m_Omega*x[i]);
double xi = x[i]-m_XOffSet;
result[0] += Math.pow(xi, 2) - this.m_A * Math.cos(this.m_Omega*xi);
}
return result;
}

6
src/eva2/server/go/problems/F7Problem.java
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@@ -65,7 +65,7 @@ public class F7Problem extends F1Problem implements java.io.Serializable {
evaluatePopulationEnd(population);
}
/** Ths method allows you to evaluate a double[] to determine the fitness
/** This method allows you to evaluate a double[] to determine the fitness
* @param x The n-dimensional input vector
* @return The m-dimensional output vector.
*/
@@ -74,11 +74,11 @@ public class F7Problem extends F1Problem implements java.io.Serializable {
result[0] = m_YOffSet;
if ((Math.floor(this.m_CurrentTimeStamp / this.m_t)%2) == 0) {
for (int i = 0; i < x.length-1; i++) {
result[0] += Math.pow(x[i], 2);
result[0] += Math.pow(x[i]-m_XOffSet, 2);
}
} else {
for (int i = 0; i < x.length-1; i++) {
result[0] += Math.pow(x[i]-this.m_Change, 2);
result[0] += Math.pow(x[i]-m_XOffSet-this.m_Change, 2);
}
}
return result;

7
src/eva2/server/go/problems/F8Problem.java
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@@ -41,12 +41,13 @@ public class F8Problem extends F1Problem implements InterfaceMultimodalProblem,
double sum1 = 0, sum2 = 0, exp1, exp2;
for (int i = 0; i < x.length; i++) {
sum1 += (x[i] - this.m_XOffSet)*(x[i] - this.m_XOffSet);
sum2 += Math.cos(c * (x[i] - this.m_XOffSet));
double xi = x[i]-m_XOffSet;
sum1 += (xi)*(xi);
sum2 += Math.cos(c * (xi));
}
exp1 = -b*Math.sqrt(sum1/(double)this.m_ProblemDimension);
exp2 = sum2/(double)this.m_ProblemDimension;
result[0] = a + Math.E - a * Math.exp(exp1)- Math.exp(exp2);
result[0] = m_YOffSet + a + Math.E - a * Math.exp(exp1)- Math.exp(exp2);
return result;
}

11
src/eva2/server/go/problems/F9Problem.java
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@@ -3,13 +3,6 @@ package eva2.server.go.problems;
import eva2.server.go.individuals.AbstractEAIndividual;
import eva2.server.go.individuals.ESIndividualDoubleData;
/**
* Created by IntelliJ IDEA.
* User: streiche
* Date: 30.06.2005
* Time: 13:59:12
* To change this template use File | Settings | File Templates.
*/
public class F9Problem extends F1Problem implements java.io.Serializable {
public F9Problem() {
@@ -32,9 +25,9 @@ public class F9Problem extends F1Problem implements java.io.Serializable {
*/
public double[] eval(double[] x) {
double[] result = new double[1];
result[0] = 0;
result[0] = m_YOffSet;
for (int i = 0; i < x.length; i++) {
result[0] += (i+1)*Math.pow(x[i], 2);
result[0] += (i+1)*Math.pow(x[i]-m_XOffSet, 2);
}
return result;
}