7-7 Three types of customers arrive at a small airport: check baggage (30%, that is,
on for each arriving customer there is a 0.30 probability that this is a \"check-baggage\" cus-
tomer), purchase tickets (15%), and carry-on (55%). The interarrival-time distribution
for all customers combined is EXPO(1.3); all times are in minutes and the first arrival is
at time 0. The bag checkers go directly to the check-bag counter to check their bags-
the time for which is distributed TRIA(2, 4, 5)-proceed to X-ray, and then go to the
gate. The ticket buyers travel directly to the ticket counter to purchase their tickets-the
time for which is distributed EXPO(7)-proceed to X-ray, and then go to the gate. The
carry-ons travel directly to the X-ray, then to the gate counter to get a boarding pass-
the time for which is distributed TRIA(1, 1.6, 3). All three counters are staffed all the
time with one agent each. The X-ray time is EXPO(1). All travel times are EXPO(2), ex-
cept for the carry-on time to the X-ray, which is EXPO(3). Run your model for a single
replication of length 920 minutes, and collect statistics on resource utilization, queues,
and system time from entrance to gate for all customers combined. For the output sta-
tistics requested, put a text box inside your Arena file, or paste in a partial screenshot
from Arena or another application that provides the requested results. For \"queues\" and
\"system time\" report both the average and maximum.