Algorithm for best sum combination from 3 groups list

I have multi group of data like:

X <-  c(2,3,5,10,15) 
Y <- c(4,6,23,15,12) 
Z <- c(23,34,12,1,5)  

and a target: target = 50

I want to know the best (for example): 2 values from X (call it X2), 4 values from Y (Y4) and 3 values from Z (Z3) that if I sum them I get sum(X2) + sum(Y4) + sum(Z3) = 50 (or the closest to 50).

Is there a solution to this problem?

The best way to use combinations is to use the function I've found on stackoverflow (can't find the post)

getVariant <- function(id, vars) {
  if (!is.list(vars)) stop('vars needs to be a list!')
  nv <- length(vars)
  lims <- sapply(vars, length)
  if (any(id > prod(lims))) stop('id above the number of combinations!')
  res <- vector("list", nv)
  for(i in nv:2) {
    f <- prod(lims[1:(i-1)])
    res[[i]] <- vars[[i]][(id - 1)%/%f + 1]
    id <- (id - 1)%%f + 1
  }

  res[[1]] <- vars[[1]][id]

  names(res) <- names(vars)
  return(as.data.frame(res))
}

It returns the combination number "id"... Is there a way to use it to get all the combinations and thus get the sum I want?

Edit: The data I've provided is just an example… My end goal is to reproduce it on a large data.