Now that your model has been created, let's explore it to answer practical optimization questions.

What is the minimum number of tables needed so that no customers are quitting waiting for a table during a four-hour period?

You will need to run the model with incrementally more tables and check in the console when the number of customers served stops increasing.

The code below resets the variables, creates the SimPy environment, modifies the resource object with a different number of tables, and adds processes before running the model - just like you did before (see code below).

random.seed(42)
customers_served = 0
customers_quiting_waiting = 0

env_my_model = simpy.Environment()
tables_my_model = simpy.Resource(env_my_model, capacity=2)
env_my_model.process(source_my_model(env_my_model, NEW_CUSTOMERS, INTERVAL_CUSTOMERS, tables_my_model))
env_my_model.run(until=60*4)
print(f"Total number of servings: {customers_served:02d}")
print(f"Total number of customers quiting waiting: {customers_quiting_waiting:02d}")

Note that your model contains randomizing functions, which we will cover in future videos, so we need to use random.seed(RANDOM_SEED) to initialize the random number generator and enable a deterministic answer to this exercise - we've set RANDOM_SEED=42.

Building a discrete-event model with SimPy

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