Demirel, Soner

This study aims to manage air traffic flow in the terminal maneuvering area (TMA) of Istanbul Sabiha Gokcen Airport by generating delay-based solutions. For this purpose, a mixed-integer mathematical modeling technique is used. The model is integrated into a graphical user interface that includes two modules: Generic Data and Real Data. In this way, planning air traffic controllers can gain foresight into the traffic flow within the TMA by using parameters derived from the traffic outside the TMA. Through the Generic Data module, preliminary runs with different traffic mixes allow researchers to observe the outcomes of various scenarios, while the Real Data module provides both planning support and delay-based recommendations for controllers. The interface includes a Gantt chart, a heatmap visualizing delays between waypoints, the frequency of radio usage by air traffic controllers for solutions, emission-related graphs and tables presenting statistics such as flight durations of aircraft within the TMA. By using the model and the interface, traffic flow can be managed optimally with the objective of minimizing delays. At the same time, the user-friendly interface offers visual references and can serve as an easy-To-use assistant for planning controllers.

Demirel, Soner

This paper investigates the reduction of airborne delays in Terminal Maneuvering Areas (TMAs) through departure time adjustments based on hotspot levels at origin airports. While existing studies primarily focus on reducing airborne delays to support environmentally sustainable airport operations, this research proposes shifting such delays to the ground within the predefined capacity limits of critical areas (hotspots) at destination airports. Istanbul Sabiha Gokcen International Airport (LTFJ), its associated TMA routes and Point Merge System (PMS) were selected as the case study. Four virtual origin airports were defined for analysis. The proposed model represents hotspot locations (gates, taxiways, and runway holding positions) as virtual nodes with predefined congestion levels (low, medium, and high). The problem is formulated as a mixed integer linear programming model and solved using the CPLEX solver. The model achieves computational efficiency within reasonable solution times. Under the implementability bound in Eq. (31), the model reduces average airborne delay from 1552 s to 931.2 s and it corresponds to a 40 percent reduction within the prescribed acceptability band. Overall, the findings demonstrate that the proposed methods align with existing literature by enhancing delay management through realistic modeling at hotspot points.