hgaoptim: GA + optim hybridization function

In adana: Adaptive Nature-Inspired Algorithms for Hybrid Genetic Optimization

GA + optim hybridization function

Description

This function allows GA to hybridize with methods in the optim general-purpose optimization function for n-variable problems in R's basic stats package (R Core Team, 2021).

Usage

hgaoptim(genpop, fitfunc, hgaparams,
                    hgaftype, hgans, ...)

Arguments

genpop	A matrix of individuals in the current population and their fitness values.
fitfunc	Fitness function
hgaparams	A list of parameters defined for use by the Optim function.
hgaftype	Types of fitness to transfer. w: individuals with the worst fitness value b: individuals with the best fitness value r: randomly selected individuals
hgans	Number of individuals to be transferred to the Optim.
...	Further arguments passed to or from other methods.

Value

A matrix containing the updated population.

Author(s)

Zeynel Cebeci & Erkut Tekeli

References

R Core Team. (2021). R: A language and environmental for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

See Also

hgaoptimx, hgaroi

Examples

hgaparams = list(method="Nelder-Mead", poptim=0.05, pressel=0.5,
  control = list(fnscale=1, maxit=100))
n = 5                   # Size of population 
m = 2                   # Number of variables
lb = c(-5.12, -5.12)    # Lower bounds for sample data
ub = c(5.12, 5.12)      # Upper bounds for sample data
genpop = initval(n, m, lb=lb, ub=ub) # Sample population
fitfunc = function(x, ...) 2*(x[1]-1)^2 + 5*(x[2]-2)^2 + 10
fitvals = evaluate(fitfunc, genpop[,1:m])
genpop[,"fitval"]=fitvals
genpop
newpop = hgaoptim(genpop, fitfunc, hgaparams, hgaftype="r", hgans=3)
newpop

adana documentation built on March 18, 2022, 6:03 p.m.