library(genalg)

dataset <- data.frame(item = c("pocketknife", "beans", "potatoes", "unions", "sleeping bag", "rope", "compass"),
                      survivalpoints = c(10, 20, 15, 2, 30, 10, 30),
                      weight = c(1, 5, 10, 1, 7, 5, 1))
weightlimit <- 20

chromosone <- c(1, 0, 0, 1, 1, 0, 0)
dataset[chromosone == 1, ]

evalFunc <- function(x)
{
  current_solution_survivalpoints <- x %*% dataset$survivalpoints
  current_solution_weight <- x %*% dataset$weight

  if (current_solution_weight > weightlimit)
    return(0)
  else
    return(-current_solution_survivalpoints)
}

iter <- 100
GAmodel <- rbga.bin(size = 7, popSize = 58, iters = iter, mutationChance = 0.01, elitism = T, evalFunc = evalFunc)

cat(summary(GAmodel))
dataset[c(1,1,0,1,1,1,1) == 1,]
plot(-GAmodel$best, type="l", col="red")
lines(-GAmodel$mean, col="blue")

c(1,0,0,0,1,0)
a <- "0"
b <- "1"
b <- paste(a, b, sep="")

strtoi("001111000000", base=2)