selsscale: Sigma Scaling

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

Sigma Scaling

Description

Sigma Scaling is based on the mean rather than the worst fitness value as in Window Scaling. In Sigma Scaling, an individual's fitness is a function of the population mean and population standard deviation (Forrest, 1985; Goldberg, 1989).

Usage

selsscale(fitvals, ns, selc, ...)

Arguments

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

Value

The indices of randomly selected individuals are returned.

Author(s)

Zeynel Cebeci & Erkut Tekeli

References

Forrest, S. (1985). Documentation of prisoner's dilemma and norms programs that use the genetic algorithm. Technical report, University of Michigan.

See Also

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

Examples

fitvals = c(6.1, 3.5, 6.2, 4.4, 5.2)
cnames = paste0("C",1:length(fitvals))
matpool = selsscale(fitvals, selc=2)
cat(cnames[matpool],"\n")

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