Expand description
The selection phase, where chromosomes are lined up for pairing in the crossover phase, dropping the chromosomes outside of the target_population_size.
The replacement_rate is the target fraction of the population which exists of children. Generational Replacement and Steady-State Replacement can both be modelled with this parameter by setting it respectively to 1.0 and 0.2-0.8. High values converge faster, but risk losing good solutions. Low values convergence slower. If there is a shortage of population after the ideal fraction, firstly remaining non-selected children and secondly remaining non-selected parents will be used to fill the shortage to avoid population collapse.
The elitism_rate is a non-generational elite gate, which ensures passing of the
best chromosomes before selection and replacement takes place. Value should
typically be very low, between 0.01 and 0.05. Relevant for
SelectTournament where the best chromosome is not guaranteed to be
selected for a tournament if the population_size is larger than the
target_population_size
Structs§
- Select
Elite - Simply sort the chromosomes with fittest first. Then take the target_population_size (or full population when in shortage) of the populations best and drop excess chromosomes. This approach has the risk of locking in to a local optimum.
- Select
Tournament - Run tournaments with randomly chosen chromosomes and pick a single winner. Do this untill the target_population_size (or full population when in shortage) of the population is reached and drop excess chromosomes. This approach kind of sorts the fitness first, but not very strictly. This preserves a level of diversity, which avoids local optimum lock-in.