seldet: Deterministic Selection

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

Deterministic Selection

Description

Deterministic Selection is similar to Remainder Stochastic Selection. The expected value of each individual in the mating pool is calculated. Individuals are copied directly into the mating pool by the exact number of expected values. Then, sorting is done according to the fraction part of the expected values. In this case, the individuals with the highest fractions go to the top of the list to be selected. The number of individuals required to complete the mating pool to population size is selected by going from the beginning of the list to the end.

Usage

seldet(fitvals, ns, ...)

Arguments

fitvals	Vector of fitness values belonging to individuals
ns	Number of individuals to be selected
...	Further arguments passed to or from other methods.

Value

The indices of randomly selected individuals are returned.

Author(s)

Zeynel Cebeci & Erkut Tekeli

See Also

select, selrand, selrswrp, selrws, selrws2, selrss, selsus, selwscale, selsscale, selsscale2, sellscale, selrscale, selrscale2, selpscale, selescale, seltour, seltour2

Examples

fitvals = c(6, 1, 2, 4, 5)
cnames = paste0("C",1:length(fitvals))
matpool = seldet(fitvals)
cat("Selected chromosomes: ", cnames[matpool], "\n")

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