operators: operators

In changepointGA: Changepoint Detection via Modified Genetic Algorithm

operators

Description

A list object contains the GA or IslandGA operators function names.

Arguments

population	It could be a function or a matrix. The function should be designed for initializing a population. The default population initialization is random initialization with some imposed constraints. See random_population for example. The function returned object is a matrix, pop. The users can specified their own population function. It could also be a matrix object, which contain the user specified chromosome. By default, each column represents one individual chromosome.
selection	A function can help select mom and dad from current generation population, where dad is set to have better fit (smaller fitness function values). The default for selection uses the linear rank selection method. See selection_linearrank for example. The function returned object is a list contain the chromosomes for mom and dad.
crossover	A function can apply crossover to the chosen parents to produce child for next generation with specified probability. The default for crossover uses the uniform crossover method. See uniformcrossover for details in the default crossover operator. The function returned object is a vector contain the chromosomes for child.
mutation	A function can apply mutation to the produced child with the specified probability Pmutation in GA_param and IslandGA_param. See mutation for details in the default mutation operator.

References

Lu, Q., Lund, R., & Lee, T. C. (2010). An MDL approach to the climate segmentation problem. Ann. Appl. Stat. 4 (1) 299 - 319.

See Also

See Also as GA.

Examples

operators = list(population = "random_population",
                 selection  = "selection_linearrank",
                 crossover  = "uniformcrossover",
                 mutation   = "mutation")

changepointGA documentation built on June 8, 2025, 1:12 p.m.