Package net.bmahe.genetics4j.core

Interface Fitness<T extends Comparable<T>>

Type Parameters:
T - the type of the fitness value, must be comparable for selection operations
Functional Interface:
This is a functional interface and can therefore be used as the assignment target for a lambda expression or method reference.
@FunctionalInterface public interface Fitness<T extends Comparable<T>>
Functional interface for evaluating the fitness of a genotype in an evolutionary algorithm.

The fitness function is a crucial component of evolutionary algorithms as it determines the quality or performance of individual solutions. It maps a genotype to a fitness value that can be used for selection, ranking, and determining evolutionary progress.

Implementations should be:

  • Deterministic: The same genotype should always produce the same fitness value
  • Thread-safe: May be called concurrently from multiple threads
  • Fast: Called frequently during evolution, performance matters

Common fitness function patterns:

  • Minimization: Lower values indicate better solutions (errors, costs)
  • Maximization: Higher values indicate better solutions (profits, accuracy)
  • Multi-objective: Use FitnessVector from the MOO module for multiple objectives
See Also:

  • Method Summary

    Modifier and Type
    Method
    Description
    T
    compute(Genotype genotype)
    Computes the fitness value for the specified genotype.

  • Method Details

    • compute

      T compute(Genotype genotype)
      Computes the fitness value for the specified genotype.

      This method should evaluate how well the genotype solves the problem and return a comparable fitness value. The interpretation of "better" depends on whether the optimization is for minimization or maximization.

      Parameters:
      genotype - the genotype to evaluate
      Returns:
      the fitness value representing the quality of the genotype
      Throws:
      RuntimeException - if evaluation fails due to invalid genotype or computation error