Crate mate_selection

A collection of mate selection methods for evolutionary algorithms

Structs

Normalized

Normalize the fitness scores into a standard normal distribution. First the scores are normalized into a standard distribution and then they are shifted by the cutoff, which is naturally measured in standard deviations. All scores which are less than the cutoff (now sub-zero) are discarded and those individuals are not permitted to mate. Finally the scores are divided by their sum to yield a selection probability. This method improves upon the proportional method by controlling for the magnitude and variation of the fitness scoring function.

Percentile

Apply a simple percentile based threshold to the population. Mating pairs are selected with uniform random probability from the eligible members of the population.

Proportional

Select parents with a probability that is directly proportional to their score.

Random

Select parents with a uniform random probability, ignoring the scores.

RankedExponential

Select parents based on their ranking in the population, with an exponentially weighted bias towards better ranked individuals. This method can apply more selection pressure than the RankedLinear method can, which is useful when dealing with very large populations or with a very large number of offspring.

RankedLinear

Select parents based on their ranking in the population. This method sorts the individuals by their scores in order to rank them from worst to best. The sampling probability is a linear function of the rank.

Traits

MateSelection

Mate selection algorithms randomly select pairs of individuals from a population.
The sampling probability of each individuals is a function of its reproductive fitness or “score”.