Package ec.eda.dovs

Class DOVSEvaluator

java.lang.Object

ec.Evaluator

ec.simple.SimpleEvaluator

ec.eda.dovs.DOVSEvaluator

All Implemented Interfaces:

Setup, Singleton, Serializable

public class DOVSEvaluator
extends SimpleEvaluator

The DOVSEvaluator is a SimpleEvaluator to evaluate the Individual. Due to the stochastic property of the problem. An individual may not to be evaluate several times so that we can have a good assessment of it. This evaluator will make use of the statistics of fitness of each individual and determine how many evaluation are needed for a individual where we can have high confidence about its fitness value.

See Also:

• Serialized Form

Field Summary

Fields inherited from class ec.simple.SimpleEvaluator

C_AUTO, cloneProblem, MERGE_BEST, MERGE_MEAN, MERGE_MEDIAN, mergeForm, numTests, P_CHUNK_SIZE, P_CLONE_PROBLEM, P_MERGE, P_NUM_TESTS, pool, V_AUTO, V_BEST, V_MEAN, V_MEDIAN

Fields inherited from class ec.Evaluator

masterproblem, P_IAMSLAVE, P_MASTERPROBLEM, p_problem, P_PROBLEM, runComplete

Constructor Summary

Constructors

Constructor	Description
DOVSEvaluator()

Method Summary

Modifier and Type	Method	Description
protected void	evalPopChunk(EvolutionState state, int[] numinds, int[] from, int threadnum, SimpleProblemForm p)	For each of the iteration, we are not just evaluate the individuals in current population but also current best individual and individuals in activeSolutions.

Methods inherited from class ec.simple.SimpleEvaluator

evalPopChunk, evaluatePopulation, runComplete, setup

Methods inherited from class ec.Evaluator

closeContacts, initializeContacts, postEvaluationGlobalUpdate, postEvaluationLocalUpdate, reinitializeContacts, setRunComplete

Methods inherited from class java.lang.Object

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

Constructor Details

DOVSEvaluator

public DOVSEvaluator()

Method Details

evalPopChunk

protected void evalPopChunk(EvolutionState state,
 int[] numinds,
 int[] from,
 int threadnum,
 SimpleProblemForm p)

For each of the iteration, we are not just evaluate the individuals in current population but also current best individual and individuals in activeSolutions. Their number of evaluation is determined by there fitness statistics.