Class NegativeCostFitnessFunction<T extends Copyable<T>>
- Type Parameters:
T- The type of object under optimization.
IntegerCostOptimizationProblem. However, the evolutionary algorithms in the library require a fitness function such that higher fitness implies better solution. Furthermore, some selection operators further assume that fitness values are positive, such as
This class transforms the cost of solution s to fitness with the following transformation:
fitness(s) = -cost(s), where cost(s) refers to the
Because this transformation produces negative fitness values, it is not compatible with all
selection operators. However, many of the selection operators in the library work even with
negative fitness values, such as any selection operator that uses only relative fitness values.
TournamentSelection and other selection operators that only care if one
fitness is higher or lower than another will work fine with negative fitness values.
Incompatible Selection Operators: The library does include some selection operators
that require positive fitness values. Thus, the NegativeIntegerCostFitnessFunction is
incompatible with such selection operators, which include the following:
BiasedStochasticUniversalSampling. The behavior
of these selection operators that select population members with probabilities that are
proportional to their fitness is undefined for negative fitnesses.
Nested Class Summary
NegativeCostFitnessFunctionConstructs a fitness function that transforms the cost of solution s to fitness with the following transformation: fitness(s) = -cost(s).
problem- The optimization problem.
fitnesspublic double fitness
(T candidate)Description copied from interface:
FitnessFunction.DoubleComputes the fitness of a candidate solution to a problem, for use by genetic algorithms and other evolutionary algorithms.
getProblemDescription copied from interface:
FitnessFunctionGets a reference to the problem that this fitness function is for.