Package org.moeaframework.problem.single

Class Ackley

java.lang.Object

org.moeaframework.problem.AbstractProblem

org.moeaframework.problem.single.Ackley

All Implemented Interfaces:

AutoCloseable, Named, Problem

public class Ackley
extends AbstractProblem

The single-objective Ackley problem with an optimum at x = (0, 0) with f(x) = 0.

References:

1. Ackley, D. H. (1987) "A Connectionist Machine for Genetic Hillclimbing", Kluwer Academic Publishers, Boston MA.

Field Summary

Fields inherited from class org.moeaframework.problem.AbstractProblem

numberOfConstraints, numberOfObjectives, numberOfVariables

Constructor Summary

Constructors

Constructor	Description
Ackley()	Constructs a new instance of the Ackley problem.

Method Summary

Modifier and Type	Method	Description
void	evaluate(Solution solution)	Evaluates the solution, updating the solution's objectives in place.
NondominatedPopulation	getReferenceSet()	Returns the reference set, typically a single solution unless the problem has multiple local minima, for this single objective problem.
Solution	newSolution()	Returns a new solution for this problem.

Methods inherited from class org.moeaframework.problem.AbstractProblem

close, getNumberOfConstraints, getNumberOfObjectives, getNumberOfVariables

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.moeaframework.problem.Problem

getName, isType

Constructor Details

Ackley

public Ackley()

Constructs a new instance of the Ackley problem.

Method Details

evaluate

public void evaluate(Solution solution)

Description copied from interface: Problem

Evaluates the solution, updating the solution's objectives in place. Algorithms must explicitly call this method when appropriate to evaluate new solutions or reevaluate modified solutions.

Parameters:

solution - the solution to be evaluated

newSolution

public Solution newSolution()

Description copied from interface: Problem

Returns a new solution for this problem. Implementations must initialize the variables so that the valid range of values is defined, but typically leave the actual value at a default or undefined state.

Returns:

a new solution for this problem

getReferenceSet

public NondominatedPopulation getReferenceSet()

Returns the reference set, typically a single solution unless the problem has multiple local minima, for this single objective problem.

Returns:

the reference set