SEMS Research Highlights 2015: Improving the Soekarno Hatta International Airport Utilization as the Main Gate of Indonesia

With the steady economic growth for the last ten years in Indonesia has made people mobility across the nation is at all time high. This is why, that most airport in Indonesia is operated more than its capacity. Soekarno Hatta International Airport (SHIA) is currently operated twice than its designed capacity. This problem has strong influence to the level of service of the airport, which next could lead to the decreasing of the passenger’s satisfaction (Yan, Shieh, & Chen, 2002). The challenges of the airport operator are to do further investment and to optimize the utilization of current ability.

Based on a research done by Redaksi Angkasa (2014), the current maximum traffic capacity of SHIA is 72 landing-takeoff traffics per one hour. They found that this still could be improved till 86 landing-takeoff traffics per one hour. Another standing point is more than 40% flights in SHIA is being parked in the remote area. The remote area is basically the aircraft parking area, located far away from the terminal building.

SEMS was trying to solve this problem, because we believe the better service from gated flights could maintain the image of SHIA as the main gate of Indonesia. There are some researches already studied about this topic. Bennel, Mesgarpour, & Potts (2011) have done a research focus on developing an optimization model. The objective of the study is to maximize the number of flights. Another research was done by integrating the runway allocation and gate assignment problem to maximize the number of flights could be accommodated in an airport (Nahry, T., & Y.J., 2013). Additionally, SEMS saw a research opportunity not to focus on operator’s perspective only, but also on the passenger’s perspective such as minimizing flight tardiness and minimizing passenger walking distance in the terminal.

This research is basically focusing on developing an optimization combination model of runway and gate assignment. The output of this research is to generate to most optimal runway and gate schedule concerns on 4 objectives, such as maximizing landing-takeoff traffics, minimizing flight tardiness, minimizing flights being parked in remote area, and minimizing passenger walking distance in airport. The model is done using the Genetic Algorithm Optimization Approach. The Genetic Algorithm it self is a metaheuristics algorithm, functioning to generate the best solution in a certain solution space of a certain problem.

Using the model, a significant reduction on un-gated flight has been achieved which reduce the traveling distance of the passenger.

This research is Conducted by Gede Arya Satya Dharma, Aziiz Sutrisno, Armand Omar Moeis, and Akhmad Hidayatno

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