A comprehensive data-driven MCDM approach to determine the best single objective function for the aircraft sequencing and scheduling problem

DÖNMEZ K., BAKIR M., ÇEÇEN R. K.

EXPERT SYSTEMS WITH APPLICATIONS, cilt.296, 2026 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 296
  • Basım Tarihi: 2026
  • Doi Numarası: 10.1016/j.eswa.2025.129172
  • Dergi Adı: EXPERT SYSTEMS WITH APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

The aircraft sequencing and scheduling problem (ASSP) is a complex optimization problem, which becomes increasingly difficult to solve as the number of aircraft and objective increases. While metaheuristic approaches have been used to produce near-optimal solutions in a reasonable amount of time, these solutions may not be sufficient and detailed for the tactical planning phase of air traffic management (ATM). To obtain optimal solutions, exact solution methods such as mixed integer programming (MIP) or integer programming (IP) are often used; however, these approaches are computationally inefficient, and the solution time increases as the number of objectives in the problem increases. However, as there are several stakeholders in the ATM system, ASSP should include several objectives. To address this challenge, a multi criteria decision-making (MCDM) approach was proposed in this study to identify the single objective that provides the best overall results for all stakeholders. The ASSP was modeled using MIP, with the Istanbul Sabiha Gok & ccedil;en Airport (LTFJ) airspace and runway structure integrated as a case study. 120 different traffic samples were run, and the results were quantified based on eight different objective functions evaluated in terms of 17 different criteria commonly used in the literature. A data-driven approach, namely Method based on the Removal Effects of Criteria (MEREC), was used to weight the criteria, and the Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) method was used to rank and validate the effectiveness of the objective functions. In addition, a rigorous two-fold sensitivity analysis considering simulated criteria weights and comparative analyses was performed at the end of the study. The results indicated that the minimization of average delay was the most significant objective function based on the current criteria, followed by the minimization of total flight times. This approach can be useful for decision-makers when trying to select or evaluate the trade-offs between different objectives in the ASSP.