Module genetic 

The module with genetic algorithm implementation.

Terms

• “chromosomes” are points in the search space. Usually chromosome is single value or vector of values.
• “Fitness” is value of goal function value in genetic algorithm.
• “Generation” is iteration number of genetic algorithm.
• “Individual” is agent in genetic algorithm (point in the search space and value of goal function).

Modules

creation

The module with algorithms with initial creation of individuals

cross

The module with most usable algorithms of crossing for various types. The module contains struct which implements the Cross trait and functions to cross chromosomes various types.

mutation

The module with most usable algorithms of mutations for various types. The module contains struct which implements the Mutation trait to mutate chromosomes various types.

pairing

The module with pairing algorithm traits. The pairing algorithm selects individuals for crossing.

pre_birth

The module with PreBirth trait implementations.

selection

The module with selection algorithms.

Structs

GeneticOptimizer

The main struct for an user. GeneticOptimizer implements Optimizer trait and keep all parts of genetic algorithm as trait objects: Creator, Pairing, Cross, Mutation, Selection, StopChecker and, if needed, Logger. The trait run genetic algorithm.

Individual

Struct for single point (agent) in the search space

Population

Stores all individuals for current generation.

Traits

Creator

The trait to create initial individuals for population.

Cross

The trait with cross algorithm.

Mutation

The trait with mutation algorithm.

Pairing

The trait to select individuals to pairing.

PreBirth

The trait may be used after mutation but before birth of the individuals.

Selection

The trait with selection algorithm.