NA's Produced When Number of Iterations Increase

[omario]

I am trying to write a function that generates random paths for a Travelling Salesman Problem.

Here is the data:

final_data = data.frame(Longitude = rnorm(19, 40,1), Lattitude = rnorm(19, -65,1))

 final_data$id = 1:19


N <- nrow(final_data)

dists <- outer(seq_len(N), seq_len(N), function(a,b) {
    geosphere::distHaversine(final_data[a,1:2], final_data[b,1:2]) })

D <- as.matrix(dists)

####


d = 19
fix_num <- 1

Here is the function for 100 random paths:

results <- list()
resultss <- list()


for (i in 1:100)

{
start.time <- Sys.time()



iteration = i

relations_i = tibble(
  from = c(fix_num, sample(setdiff(1:d, fix_num))),
  to = lead(from, default=from[1]),
)

relations_i = data.frame(relations_i)
relations_i$iteration = i

m<-dists

my_sums_i = function(relations_i, m) {
  r = as.matrix(relations_i)
  if(mode(r) != "numeric") mode(r) = "numeric"
  sum(m[r])}

m_i = my_sums_i(relations_i, m)

end.time <- Sys.time()
time.taken_i <- end.time - start.time

m_i$time = time.taken_i

 results[[i]] <- m_i

 resultss[[i]] <- relations_i

}

results_1 <- data.frame(do.call(rbind.data.frame, results))
results_2 <- data.frame(do.call(rbind.data.frame, resultss))


####

This seems to work fine - the problem happens when I Increase the number of paths (e.g. i =100 vs. i = 1000):

results <- list()
resultss <- list()


for (i in 1:1000)

{
start.time <- Sys.time()



iteration = i

relations_i = tibble(
  from = c(fix_num, sample(setdiff(1:d, fix_num))),
  to = lead(from, default=from[1]),
)

relations_i = data.frame(relations_i)
relations_i$iteration = i

m<-dists

my_sums_i = function(relations_i, m) {
  r = as.matrix(relations_i)
  if(mode(r) != "numeric") mode(r) = "numeric"
  sum(m[r])}

m_i = my_sums_i(relations_i, m)

end.time <- Sys.time()
time.taken_i <- end.time - start.time

m_i$time = time.taken_i

 results[[i]] <- m_i

 resultss[[i]] <- relations_i

}

results_1 <- data.frame(do.call(rbind.data.frame, results))
results_2 <- data.frame(do.call(rbind.data.frame, resultss))

• For some reason, when there are more paths, NA's are produced in the results.
• Is there a way to fix this?

Thank you!