brkga: BRKGA Algorithm

In leandromarino/BRKGApp: What the package does (short line)

Description

This function applies brkga algorithm to solve a problem considering problem-dependent objective function and decoder

Usage

brkga

Arguments

data	Vector or Matrix (data to calculate objective function)
popSize	Number of chromosomes (elements) in the population
Rcpp	Use Rcpp code? (default = FALSE)
pelite	Percentual of elite chromosomes
pmutation	Percentual of mutant chromosomes
pcrossover	Crossover probability

Format

An object of class function of length 1.

Details

brkga

Author(s)

Leandro Marino ([e-mail])

References

Gonçalves, J.F., Resende, M.G.C. Biased random-key genetic algorithms for combinatorial optimization. J Heuristics 17, 487–525 (2011). <https://doi.org/10.1007/s10732-010-9143-1>

Gonçalves J.F., Resende M.G.C. (2018) Biased Random-Key Genetic Progamming. In: Martí R., Pardalos P., Resende M. (eds) Handbook of Heuristics. Springer, Cham. <https://doi.org/10.1007/978-3-319-07124-4_25>

Examples

data(iris)
t_brkga <- BRKGApp::brkga(iris[, -5], Rcpp = TRUE)
t_brkga
genpop_R(t_brkga)
genpop_Rcpp(t_brkga)
genpop(t_brkga)

genmut(t_brkga)
genmut_R(t_brkga)
genmut_Rcpp(t_brkga)

leandromarino/BRKGApp documentation built on Dec. 21, 2021, 9:47 a.m.