This project simulates the check-in area of an airport, which is usually an area that sees high passenger traffic. Our aim is to analyze different queue configurations in order to determine the best policy that should be used to make costumers happy. The underlining assumption it's that airport passengers will choose one company over another based on the wait in the check-in queues. If the wait it's too long a passenger will probably choose another company for her/his next flight. It should also be taken into consideration that, given the current covid-19 emergency, the delays can be increased due to the necessary covid test that all passengers without green pass should perform.

The available queue configurations are:

• SINGLE - Only one queue in which all passenger will be enqueued in FIFO (First In First Out) order. When an officer it's available, picks the first element from the queue
• MULTI - One FIFO queue for each officer. When a passenger arrives, she/he can choose the queue with the least number of enqueued passengers
• SITA - 3 FIFO queues for 3 different types of passengers (Online, National, International check-in). When a passenger arrives, she/he is enqueued in the corresponding queue based on the service type

All three configurations can be used to simulate the check-in area, while the covid test area can be simulated using only the first two, since there's no correlation between the test and the check-in type.

The demo.c file in the ./lib folder can be used to simulate all three configurations with and without the covid test area. The simulation can be configured by varying the arrival rate, service rate, probability of having a green pass, etc.

This project can be configured through the constants defined in the config.h file in the root directory.

• FILENAME : name of the file where the result will be written (ex. "filename.csv")
• SEED : initial seed
• STOP : simulation end time (sec)
• OFF : number of officers for the check-in queues
• ONLINEOFF : number of officers for online check-in
• NATIONALOFF : number of officers for national check-in
• INTERNATIONALOFF : number of officers for international check-in
• TESTOFF : number of officers for the test queues
• ITERATIONS: number of times the same simulation will be run

• LAMBDA_1_5 : passenger arrival rate between 1:00:01 and 5:00:00
• LAMBDA_5_9 : passenger arrival rate between 5:00:01 and 9:00:00
• LAMBDA_9_13 : passenger arrival rate between 9:00:01 and 13:00:00
• LAMBDA_13_17 : passenger arrival rate between 13:00:01 and 17:00:00
• LAMBDA_17_21 : passenger arrival rate between 17:00:01 and 21:00:00
• LAMBDA_21_1 : passenger arrival rate between 21:00:01 and 1:00:00
• ONLINEMU : online check-in passenger service rate
• NATIONALMU : national check-in passenger service rate
• INTERNATIONALMU : international check-in passenger service rate
• ONLINEP : probability of having a passenger with online check-in
• NATIONALP : probability of having a passenger with national check-in
• INTERNATIONALP : probability of having a passenger with international check-in
• MAXWAIT : maximum time a passenger is willing to wait in the queue

• TESTMU : covid test service rate
• GREENPASSP : probability of having the greenpass
• POSITIVEP : probability of being positive to the covid test
• TESTWAIT: time to wait for the covid test results (usually 15 min)

make all

./demo

make clean