ec.multiobjective.spea2
Class SPEA2Evaluator

java.lang.Object
  extended by ec.Evaluator
      extended by ec.simple.SimpleEvaluator
          extended by ec.multiobjective.spea2.SPEA2Evaluator
All Implemented Interfaces:
Setup, Singleton, java.io.Serializable

public class SPEA2Evaluator
extends SimpleEvaluator

This subclass of SimpleEvaluator evaluates the population, then computes auxiliary fitness data of each subpopulation.

See Also:
Serialized Form

Field Summary
 
Fields inherited from class ec.Evaluator
P_IAMSLAVE, P_MASTERPROBLEM, p_problem, P_PROBLEM
 
Constructor Summary
SPEA2Evaluator()
           
 
Method Summary
 double[][] calculateDistances(EvolutionState state, Individual[] inds)
          Returns a matrix of sum squared distances from each individual to each other individual.
 void computeAuxiliaryData(EvolutionState state, Individual[] inds)
          Computes the strength of individuals, then the raw fitness (wimpiness) and kth-closest sparsity measure.
 void evaluatePopulation(EvolutionState state)
          A simple evaluator that doesn't do any coevolutionary evaluation.
 
Methods inherited from class ec.simple.SimpleEvaluator
evalPopChunk, runComplete, setup
 
Methods inherited from class ec.Evaluator
closeContacts, initializeContacts, reinitializeContacts
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

SPEA2Evaluator

public SPEA2Evaluator()
Method Detail

evaluatePopulation

public void evaluatePopulation(EvolutionState state)
Description copied from class: SimpleEvaluator
A simple evaluator that doesn't do any coevolutionary evaluation. Basically it applies evaluation pipelines, one per thread, to various subchunks of a new population.

Overrides:
evaluatePopulation in class SimpleEvaluator

computeAuxiliaryData

public void computeAuxiliaryData(EvolutionState state,
                                 Individual[] inds)
Computes the strength of individuals, then the raw fitness (wimpiness) and kth-closest sparsity measure. Finally, computes the final fitness of the individuals.


calculateDistances

public double[][] calculateDistances(EvolutionState state,
                                     Individual[] inds)
Returns a matrix of sum squared distances from each individual to each other individual.