net.sourceforge.cilib.functions.continuous.moo.zdt.ZDT3 Maven / Gradle / Ivy
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package net.sourceforge.cilib.functions.continuous.moo.zdt;
import net.sourceforge.cilib.functions.ContinuousFunction;
import net.sourceforge.cilib.problem.FunctionOptimisationProblem;
import net.sourceforge.cilib.problem.MOOptimisationProblem;
import net.sourceforge.cilib.type.types.container.Vector;
/**
* Zitzler-Thiele-Deb Test Function 3
*
* Characteristics:
*
* - Convex Pareto-optimal front.
* - Discontiguous Pareto-optimal front.
*
*
*
* This function represents the discreteness feature; its Pareto-optimal front
* consists of several noncontiguous convex parts. The introduction of the sine
* function in h causes discontinuity in the Pareto-optimal front. However,
* there is no discontinuity in the parameter space.
*
*
*
* The Pareto-optimal front is formed with g(x) = 1
*
*
*
* References:
*
*
*
* -
* E. Zitzler, K. Deb and L. Thiele, "Comparison of multiobjective
* evolutionary algorithms: Empirical results", in Evolutionary Computation,
* vol 8, no 2, pp. 173-195, 2000.
*
*
*
*
*/
public final class ZDT3 extends MOOptimisationProblem {
private static final long serialVersionUID = 5783167168187614882L;
private static final String DOMAIN = "R(0:1)^30";
private static class ZDT3_h extends ContinuousFunction {
private static final long serialVersionUID = -3438306908263146396L;
private final ZDT_f1 f1;
private final ZDT_g g;
public ZDT3_h() {
this.f1 = new ZDT_f1();
this.g = new ZDT_g();
}
@Override
public Double f(Vector input) {
double f1_val = this.f1.f(input);
double g_val = this.g.f(input);
return 1.0 - Math.sqrt(f1_val / g_val) - (f1_val / g_val) * Math.sin(10.0 * Math.PI * f1_val);
}
}
private static class ZDT3_f2 extends ContinuousFunction {
private static final long serialVersionUID = 1052615620850285975L;
private final ZDT_g g;
private final ZDT3_h h;
public ZDT3_f2() {
this.g = new ZDT_g();
this.h = new ZDT3_h();
}
@Override
public Double f(Vector input) {
return this.g.f(input) * this.h.f(input);
}
}
public ZDT3() {
FunctionOptimisationProblem zdt3_f1 = new FunctionOptimisationProblem();
zdt3_f1.setFunction(new ZDT_f1());
zdt3_f1.setDomain(DOMAIN);
add(zdt3_f1);
FunctionOptimisationProblem zdt3_f2 = new FunctionOptimisationProblem();
zdt3_f2.setFunction(new ZDT3_f2());
zdt3_f2.setDomain(DOMAIN);
add(zdt3_f2);
}
public ZDT3(ZDT3 copy) {
super(copy);
}
@Override
public ZDT3 getClone() {
return new ZDT3(this);
}
}
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