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restaurant queque simulation.py
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restaurant queque simulation.py
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import simpy
import random
import statistics
import numpy as np
wait_times = []
class Restaurant(object):
def __init__(self,env, num_servers,num_cooks):
self.env = env
self.server = simpy.Resource(env, num_servers)
self.scanner = simpy.Resource(env, num_cooks)
def buy_food(self,customer):
yield self.env.timeout(np.random.exponential(1))
def cook_food(self,customer):
yield self.env.timeout(random.uniform(5,7))
def go_to_eat(env,customer,restaurant):
#Customer arrive at the restaurant
arrival_time = env.now
with restaurant.server.request() as request:
yield request
yield env.process(restaurant.buy_food(customer))
with restaurant.scanner.request() as request:
yield request
yield env.process(restaurant.cook_food(customer))
queue = env.now - arrival_time
minutes_queue, frac_minutes = divmod(queue, 1)
seconds_queue = frac_minutes * 60
print(f"The customer wait time is {minutes_queue} minutes and {seconds_queue} seconds.")
wait_times.append(env.now - arrival_time)
def run_restaurant(env, num_servers, num_cooks):
restaurant = Restaurant(env, num_servers, num_cooks)
for customer in range(10):
env.process(go_to_eat(env, customer, restaurant))
while True:
yield env.timeout(np.random.exponential(5)) #Mean interarrival rate μ1 = 0.2 minutes)
customer += 1
env.process(go_to_eat(env, customer, restaurant))
def get_user_input():
num_servers = input("Input # of cashiers: ")
num_cooks = input("Input # of cooks: ")
params = [num_servers, num_cooks]
params = [int(x) for x in params]
return params
def main():
# Setup
random.seed(69420)
num_servers, num_cooks = get_user_input()
# Run the simulation
env = simpy.Environment()
env.process(run_restaurant(env, num_servers, num_cooks))
env.run(until=100)
# View the results
average_wait = statistics.mean(wait_times)
minutes, frac_minutes = divmod(average_wait, 1)
seconds = frac_minutes * 60
print("-----------")
print(f"\nThe average wait time is {minutes} minutes and {seconds} seconds.")
#Running Simulation:
main()