set.seed(1)
# Data
Gems <- data.frame(
Color = c("Red", "Blue", "Purple", "Orange",
"Green", "Pink", "White", "Black",
"Yellow"),
Weight = round(runif(9,0.5,5),2),
Value = round(abs(rnorm(9,0,5))+0.5,2),
Times=c(rep(1,8),0)
)
head(Gems)
# \donttest{
# Task: Gem selection.
# Aim: Get highest combined value.
# Restriction: Max weight of the gem combined = 10.
res0<-evolafit(cbind(Weight,Value)~Color, dt= Gems,
# constraints: if greater than this ignore
constraintsUB = c(10,Inf),
# constraints: if smaller than this ignore
constraintsLB= c(-Inf,-Inf),
# weight the traits for the selection
b = c(0,1),
# population parameters
nCrosses = 100, nProgeny = 20, recombGens = 1,
# coancestry parameters
D=NULL, lambda=c(0,0), nQtlStart = 1,
# selection parameters
propSelBetween = .9, propSelWithin =0.9,
nGenerations = 50
)
bestSol(res0$pop, n=2)
# }
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