non-finite value supplied by optim

[swaheera]

I am working with R. I am trying to follow the instructions from the "gpareto" R package to optimize some arbitrary function that I defined: https://cran.r-project.org/web/packages/GPareto/GPareto.pdf

Here is the function (7 inputs, 4 outputs):

library(gpareto)
library(dplyr)

# create some data for this example
    a1 = rnorm(1000,100,10)
    b1 = rnorm(1000,100,5)
    c1 = sample.int(1000, 1000, replace = TRUE)
    train_data = data.frame(a1,b1,c1)

funct_set <- function (x) {
    x1 <- x[1]; x2 <- x[2]; x3 <- x[3] ; x4 <- x[4]; x5 <- x[5]; x6 <- x[6]; x[7] <- x[7]
    f <- numeric(4)
    
    
    #bin data according to random criteria
    train_data <- train_data %>%
        mutate(cat = ifelse(a1 <= x1 & b1 <= x3, "a",
                            ifelse(a1 <= x2 & b1 <= x4, "b", "c")))
    
    train_data$cat = as.factor(train_data$cat)
    
    #new splits
    a_table = train_data %>%
        filter(cat == "a") %>%
        select(a1, b1, c1, cat)
    
    b_table = train_data %>%
        filter(cat == "b") %>%
        select(a1, b1, c1, cat)
    
    c_table = train_data %>%
        filter(cat == "c") %>%
        select(a1, b1, c1, cat)
    
    
    
    #calculate  quantile ("quant") for each bin
    
    table_a = data.frame(a_table%>% group_by(cat) %>%
                             mutate(quant = ifelse(c1 > x[5],1,0 )))
    
    table_b = data.frame(b_table%>% group_by(cat) %>%
                             mutate(quant = ifelse(c1 > x[6],1,0 )))
    
    table_c = data.frame(c_table%>% group_by(cat) %>%
                             mutate(quant = ifelse(c1 > x[7],1,0 )))
    
    f[1] = mean(table_a$quant)
    f[2] = mean(table_b$quant)
    f[3] = mean(table_c$quant)
    
    
    #group all tables
    
    final_table = rbind(table_a, table_b, table_c)
    # calculate the total mean 
    
    f[4] = mean(final_table$quant)
    
    
    
    
    return (f);
}

I then set up the specifications for the optimization (e.g. upper and lower bounds, number of iterations):

lower=c(80,80,80,80, 100,200,300)
upper=c(120,120,120,120,200,300,400)
budget <- 25

Next, I run the optimization algorithm:

omEGO <- easyGParetoptim(fn = funct_set, budget = budget, lower = lower, upper = upper)

But this produces an error:

Error in optim(par = parinit, fn = fn, gr = gr, method = "L-BFGS-B", lower = lower,  : 
  non-finite value supplied by optim

I tried to research on the internet other instances that encountered similar errors, e.g.: "non-finite value supplied by optim" error when using betareg

But I am not sure how to apply the logic from these posts to fix my problem.

Could someone please show me what to do?
Thanks