Package net.bmahe.genetics4j.core.evaluation

Class FitnessEvaluatorBulkAsync<T extends Comparable<T>>

java.lang.Object

net.bmahe.genetics4j.core.evaluation.FitnessEvaluatorBulkAsync<T>

Type Parameters:

T -

All Implemented Interfaces:

FitnessEvaluator<T>

public class FitnessEvaluatorBulkAsync<T extends Comparable<T>>
extends Object
implements FitnessEvaluator<T>

Wrapper around FitnessBulkAsync for computing the fitness of a population

Field Summary

Fields

Modifier and Type	Field	Description
private final EAConfigurationBulkAsync<T>	eaConfigurationBulkAsync
private final ExecutorService	executorService
static final org.apache.logging.log4j.Logger	logger

Constructor Summary

Constructors

Constructor	Description
FitnessEvaluatorBulkAsync(EAConfigurationBulkAsync<T> _eaConfigurationBulkAsync, ExecutorService _executorService)

Method Summary

Modifier and Type	Method	Description
List<T>	evaluate(long generation, List<Genotype> genotypes)	Evaluates the fitness of all genotypes in the given population.

Methods inherited from class java.lang.Object

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

Methods inherited from interface net.bmahe.genetics4j.core.evaluation.FitnessEvaluator

postEvaluation, preEvaluation

Field Details

logger

public static final org.apache.logging.log4j.Logger logger

eaConfigurationBulkAsync

private final EAConfigurationBulkAsync<T extends Comparable<T>> eaConfigurationBulkAsync

executorService

private final ExecutorService executorService

Constructor Details

FitnessEvaluatorBulkAsync

public FitnessEvaluatorBulkAsync(EAConfigurationBulkAsync<T> _eaConfigurationBulkAsync,
 ExecutorService _executorService)

Method Details

evaluate

public List<T> evaluate(long generation,
 List<Genotype> genotypes)

Description copied from interface: FitnessEvaluator

Evaluates the fitness of all genotypes in the given population.

This is the core method that computes fitness values for an entire population of genotypes. The implementation strategy (synchronous, parallel, asynchronous) is determined by the specific evaluator implementation.

Requirements:

• Return fitness values in the same order as input genotypes
• Return exactly one fitness value per input genotype
• Ensure fitness values are comparable for selection operations
• Handle empty populations gracefully (return empty list)

The generation parameter can be used for:

• Adaptive fitness functions that change over time
• Logging and monitoring evaluation progress
• Implementing generation-specific evaluation strategies
• Debugging and performance analysis

Specified by:

evaluate in interface FitnessEvaluator<T extends Comparable<T>>

Parameters:

generation - the current generation number (0-based)

genotypes - the population of genotypes to evaluate

Returns:

a list of fitness values corresponding to each genotype