I am building a simulation in R using the simmer package.

The simulation models a restaurant where customers wait for their food after an order is placed.

Each order resource takes a different amount of time to use. Branch assigns a trajectory with a related timeout value depending on which resource was selected and records whether the resource used was digital or live for later reference. Note that this trajectory is incomplete on its own (explained later).

An order may have up to three types of products, each type having a different probability and taking a different amount of time to assemble. The limiting resource here is space to assemble orders. An assembly does not start until there is space for its tray. The trajectory is returned by the following function.

# Packages and model variables used
library(simmer)
library(simmer.plot)
library(simmer.bricks)
library(tidyr)

# (p) probability
p_rts <- 0.125 # ready to serve menu item
p_hot <- 0.25 # hot food item
p_bev <- 0.7 # Beverage

# (t) time in seconds - average from 
t_rts <- 10
t_hot <- 175
t_bev <- 25

# arrival distribution
r_arrive <- function(){
    runif(20, min = 0, max = 600) %>% # all arrivals occur within first 600 seconds
    sort
}

# The trajectory where the issue likely exists
f_order_prepare <- function(e, p_rts, p_hot, p_bev, t_rts, t_hot, t_bev){
  trajectory() %>%
    set_attribute("start_assembly", function() now(e)) %>%
    do_parallel(
      traj = list(
        trajectory() %>% branch(
          function() ifelse(runif(1) <= p_rts, 1, 2),
          continue = c(TRUE, TRUE), 
          trajectory() %>% set_attribute("has_rts", 1) %>% timeout(t_rts), 
          trajectory() %>% set_attribute("has_rts", 0)),
        trajectory() %>% branch(
          function() ifelse(runif(1) <= p_hot, 1, 2),
          continue = c(TRUE, TRUE), 
          trajectory() %>% set_attribute("has_hot", 1) %>% timeout(t_hot),
          trajectory() %>% set_attribute("has_hot", 0)),
        trajectory() %>% branch(
          function() ifelse(runif(1) <= p_bev, 1, 2),
          continue = c(TRUE, TRUE), 
          trajectory() %>% set_attribute("has_bev", 1) %>% timeout(t_bev), 
          trajectory() %>% set_attribute("has_bev", 0))
      ),
      .env = e, 
      wait = TRUE
    ) %>%
    log_("order ready") %>%
    set_attribute("order_ready", function() now(e))
}

We record when the assembly starts and then run three branches in parallel. If a product is chosen, it sets its timeout and records that it was chosen; otherwise, it records that the product was not selected. do_parallel waits for the longest of the three trajectories to complete, then continues.

trj_QSR <- trajectory() %>%
  seize("pickup_capacity", 1) %>%
  log_("seized the pick_up capacity") %>%
  simmer::join(
    f_order_prepare(env, p_rts, p_hot, p_bev, 
                  t_rts, t_hot, t_bev)
    )%>%
  timeout(20) %>% #delay for customer to collect tray
  release("pickup_capacity", 1) %>%
  set_attribute("transaction_done", function() now(env))

## Initiate
reset(env)
set.seed(12345)
env <- simmer() 
env <- env %>%
  add_resource("pickup_capacity", 12) %>%
  add_generator("transaction", trj_QSR, 
                distribution = at(r_arrive()), mon = 2)

env %>% run(until=50000000) #~578 days to ensure issues are not related to run time

The script executes without error; however, only the first 13 arrivals make it far enough to record which products were selected in do_parallel and only two finish their trajectory. The other 11 record the selections but then stop. The following code summarizes the attributes I tracked for troubleshooting.

get_mon_attributes(env) %>%
  dplyr::select(-c("time", "replication")) %>%
  pivot_wider(
    names_from = key,
    values_from = value
  ) %>%
  View(title = "atts")

Summary:
For some reason, most arrivals do not complete the do_parallel trajectories and, therefore, never release the “pickup_capacity” resource, leaving remaining arrivals in the queue.

I am looking for help isolating why this is occurring. Thanks.