Multi-objective TMA management optimization using the point merge system

Cecen R. K.

Aircraft Engineering and Aerospace Technology, vol.93, no.1, pp.15-24, 2021 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 93 Issue: 1
  • Publication Date: 2021
  • Doi Number: 10.1108/aeat-09-2019-0181
  • Journal Name: Aircraft Engineering and Aerospace Technology
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Compendex, INSPEC
  • Page Numbers: pp.15-24
  • Keywords: Aircraft sequencing and scheduling problem, Point merge system, Mixed-integer linear programming, Multi-objective optimization, RUNWAY, ARRIVAL
  • Eskisehir Osmangazi University Affiliated: Yes


© 2020, Emerald Publishing Limited.Purpose: The purpose of this study is to provide conflict-free operations in terminal manoeuvre areas (TMA) using the point merge system (PMS), airspeed reduction (ASR) and ground holding (GH) techniques. The objective is to minimize both total aircraft delay (TD) and the total number of the conflict resolution manoeuvres (CRM). Design/methodology/approach: The mixed integer linear programming (MILP) is used for both single and multi-objective optimization approaches to solve aircraft sequencing and scheduling problem (ASSP). Compromise criterion and ε-constraint methods were included in the methodology. The results of the single objective optimization approach results were compared with baseline results, which were obtained using the first come first serve approach, in terms of the total number of the CRM, TD, the number of aircraft using PMS manoeuvres, ASR manoeuvres, GH manoeuvres, departure time updates and on-time performance. Findings: The proposed single-objective optimization approach reduced both the CRM and TD considerably. For the traffic flow rates of 15, 20 and 25 aircraft, the improvement of CRM was 53.08%, 41.12% and 32.6%, the enhancement of TD was 54.2%, 48.8% and 31.06% and the average number of Pareto-optimal solutions were 1.26, 2.22 and 3.87, respectively. The multi-objective optimization approach also exposed the relationship between the TD and the total number of CRM. Practical implications: The proposed mathematical model can be implemented considering the objectives of air traffic controllers and airlines operators. Also, the mathematical model is able to create conflict-free TMA operations and, therefore, it brings an opportunity for air traffic controllers to reduce frequency occupancy time. Originality/value: The mathematical model presents the total number of CRM as an objective function in the ASSP using the MILP approach. The mathematical model integrates air traffic controllers’ and airline operators’ perspective together with new objective functions.