setupEvolutionaryOperators: Enhance control object with evolutionary operators.

In jakobbossek/ecr: Evolutionary Computing in R

Description

Define the toolbox of all the evolutionary operators you wish to operate on your problem.

Usage

setupEvolutionaryOperators(control,
  parent.selector = getDefaultEvolutionaryOperators(control$representation,
  "parent.selector"),
  survival.selector = getDefaultEvolutionaryOperators(control$representation,
  "survival.selector"),
  generator = getDefaultEvolutionaryOperators(control$representation,
  "generator"),
  mutator = getDefaultEvolutionaryOperators(control$representation,
  "mutator"),
  recombinator = getDefaultEvolutionaryOperators(control$representation,
  "recombinator"))

Arguments

control	[ecr_control] ECR control object generated via setupECRControl.
parent.selector	[ecr_selector] Selection operator which implements a procedure to copy individuals from a given population to the mating pool, i. e., allow them to become parents.
survival.selector	[ecr_selector] Selection operator which implements a procedurce to extract individuals from a given set, which should survive and set up the next generation.
generator	[ecr_generator] Generator operator of type ecr_generator for the generation of the initial population.
mutator	[ecr_mutator] Mutation operator of type ecr_mutator.
recombinator	[ecr_recombinator] Recombination operator of type ecr_recombinator.

Value

[ecr_control] Modified control object.

Note

Keep in mind, that all of the provided operators need to be compatible with the “representation” stored in the control object. There are reasonable default operators in almost any cases. Only in the case of a “custom” representation, mutator, recombintor and generator need to be set explicitly.

jakobbossek/ecr documentation built on May 18, 2019, 9:09 a.m.