Genetic Algorithm

class jmetal.algorithm.singleobjective.genetic_algorithm.GeneticAlgorithm(problem: jmetal.core.problem.Problem, population_size: int, offspring_population_size: int, mutation: jmetal.core.operator.Mutation, crossover: jmetal.core.operator.Crossover, selection: jmetal.core.operator.Selection, termination_criterion: jmetal.util.termination_criterion.TerminationCriterion = <jmetal.util.termination_criterion.StoppingByEvaluations object>, population_generator: jmetal.util.generator.Generator = <jmetal.util.generator.RandomGenerator object>, population_evaluator: jmetal.util.evaluator.Evaluator = <jmetal.util.evaluator.SequentialEvaluator object>)

Bases: jmetal.core.algorithm.EvolutionaryAlgorithm

create_initial_solutions() → List[S]

Creates the initial list of solutions of a metaheuristic.

evaluate(population: List[S])

Evaluates a solution list.

get_name() → str

get_result() → R

replacement(population: List[S], offspring_population: List[S]) → List[S]

Replace least-fit population with new individuals.

reproduction(mating_population: List[S]) → List[S]

Breed new individuals through crossover and mutation operations to give birth to offspring.

selection(population: List[S])

Select the best-fit individuals for reproduction (parents).

stopping_condition_is_met() → bool

The stopping condition is met or not.