Agent-based simulation and analysis of developed implementation for reducing passenger queue at the airport

Thanks to advancing technology and increasing human population, air transportation is being preferred much more by people every year. Due to the increasing airline demand, passenger density is experienced at the airports which are located in the tourist center cities attracting foreign and domestic tourists like Istanbul. Airlines and airport terminal companies are seeking solutions to such problems that are long passenger queues at check-in counters and passport control duties at airport having intense passenger traffic by allocating passengers more evenly. In recently years, technology has been changing and becoming more benefical to human's problem. The firms have tried to find ways to make life more easy. In modern world, the time is one of the most important things and the firms have developed new applications and tools, one of them is iBeacon Technology. iBeacon; a term used by the Apple company; BLE (Bluetooth Low Energy) beacon technology used with IOS7 base operating system. BLE beacon technology; although recognized as iBeacon technology, it is also supported by Android and Blackberry tools. Thanks to the exponential increase in smart mobile devices in recent years, new technological developments like iBeacon technology draw the attention of businesses. Features In the digital world, for the new generation of consumers who use channels such as social media extensively, the physical world and the technologies that the digital world intersects are of great importance. Beyond this fact, it creates a new channel for the messages that businesses want to deliver to consumers. In this study; critical information as position of passenger at terminal, service time of check-in desk and passport control, waiting time at check-in and passport control queue e.t.c. for analysing the system is obtained by iBeacon Technology providing huge benefit for obtaining update information of customer, product and employee according to the demands of the firms. Before implementing Beacon Technology which is recommended to solve passenger density problem, meaningful data for executive authorities is obtained by Agent Based Simulation developed for complex problem spectrum which can not be solved by Discrete Simulation Modeling. Recent developments; An Agent Based Simulation paradigm has emerged that has proved useful for problems in a wide variety of fields in biology, economics, social sciences, physics, social science and geographical simulations. In line with this new paradigm, a number of simulation programs and tools have been developed to apply Agent Based Simulation to the complex structured problem space, which can not be answered by Discrete Event Simulation. It has been understood that the Agent Based Simulation model used in the thesis study is suitable for the simulation of the decision support system application proposed for the solution of the discussed queuing problem and has been extensively used in recent studies. Since the passenger element is the basic factor of the model, it is stated that the Agent Based Simulation Models are more closely related to the other Simulation Models or System Dynamics. For the data obtained from simulation to be meaningful, the main simulation model and passenger class is formed in the light of real information which belongs to international terminal and passengers who use the international terminal taken on in this study. Furthermore, decision support system algorithm belonging to iBeacon application is developed and we probe whether passengers who have iBeacon application stay less time in system compared to normal passengers who do not have iBeacon application. The simulation model which is developed for proposed decision supporting system consists of two main parts. The first of these is the "main" section or class that covers the entire system. The section which is mentioned; the main part of the simulation; it covers all ground handling services provided to passengers at international terminals and the related variables. The second part is the "Passenger" section or class. In this section; passenger-related variables and the selection function that determines which check-in counters and passport control sections to go to. In five different scenarios for validation the simulation modeling; it is seen that the average time spent in the system of all passengers forming the main mass and passengers which is detected by the Beacon device is the same at the α = 0.05 meaning level. Results from simulation model which is based on the data obtained from the real world and provided the validity show that tha data collected by Beacon devices can represent all passengers at system with the α = 0.05 significance level. After the validity of the simulation is established; The effect of the iBeacon application on the ability of the passengers to complete their operations in the system with less waiting time than the other passengers was investigated. In addition, different scenarios were developed to determine the conditions under which the iBeacon application is used and the benefits of using it. These scenarios are based on three variables: the percentage of passengers detected with the Beacon device, the percentage of passengers using the iBeacon application, and finally the passenger density. In addition to this scenario, two different scenarios were also created to investigate the effect of iBeacon application on increase and decrease of the number of box office in the passport control section and check-in counter. In this study, 38 different simulation scenarios whose the percantege of passengers detected with Beacon device, the percentage of passenger using the iBeacon application and passenger density are different have been run and analysed the average waiting time and average staying time at system of passengers. For every simulation scenario, hypothesis tests about difference between average waiting times and average staying times of passengers who have/do not have iBeacon application have been done with the α = 0.05 significance level and obtained meaningful results to implement Beacon technology at airport for executive authorities. According to level of passenger density, we determined how much the percantege of passengers detected with Beacon device and the percentage of passenger using the iBeacon application must be at least in order to understand that decision support system is the effect of reducing waiting time at queue and staying time at system. In future studies, different results can be obtained with different algorithms than the decision support system proposed in this thesis study. In the proposed algorithm; As a result of comparing the waiting times in the queues of last passengers with the iBeacon application, the choice of the passenger's counter and passport section election is made. Progressive studies could be yield different results compared to the average waiting time of the last three passengers with iBeacon applications rather than the waiting time of the last passenger with iBeacon application.