How to define fitness_function properly in R?

Question

I'm working on Genetic Algorithms in R for optimizing KMeans and try to figure out why Im stuck on defining Fitness_function. The Fitness_Function already defined in step 3 but it won't run, it shows an error:

Error in ga(type = "real-valued", Fitness = function(params) Fitness_function(params, : A fitness function must be provided

I already tried to add another Fitness_Function but its make it worse which I cant go forward to the next step because there's same Fitness_Function

Here's what Im trying:

# Step 1: Load required libraries
library(GA)
library(cluster)
library(factoextra)
library(readxl)
# Step 2: Generate or import your data (replace this with your data)
data <- read_xlsx("C:/Users/User/Downloads/input.xlsx", 
                  col_names = FALSE)
# Step 3: Define the Fitness function (K-Means clustering quality)
Fitness_function <- function(params, data) {
  n_clusters <- 2 
  cluster_centers <- matrix(params, ncol = ncol(data), byrow = TRUE)
  kmeans_result <- kmeans(data, centers = cluster_centers, iter.max 
                          = 100)
  return(-kmeans_result$tot.withinss) 
  # Negative since GA  maximizes the Fitness
}

# Step 4: Define the search space (parameter space for cluster centers)
n_features <- ncol(data) 
# Number of features (columns) in 'data'
search_space <- matrix(rep(c(min(data), max(data)), n_features), 
                       nrow = 2)
# Step 5: Run the Genetic Algorithm with more runs and a larger population size

ga_result <- ga(type = "real-valued", 
                Fitness = function(params) Fitness_function(params, data), 
                lower = search_space[1, ], 
                upper = search_space[2, ],
                maxiter = 200, 
                run = 200,
                popSize = 100, 
                # Increase the population size for the GA
                pCrossover = 0.8, 
                pMutation = 0.1, 
                elitism = 1 

)