A stochastic multi-objective programming model for the runway scheduling problem in the airport with the parallel point merge system and multiple runways

The Point Merge System (PMS) was introduced in 2006 after a series of real-time simulations conducted at the EUROCONTROL Experiment Center (EEC). This system allows the systematic sequencing of aircraft in the terminal maneuvering area. The Parallel-Point Merge System (P-PMS) was later implemented at busy airports by deploying two opposite PMSs. In the P-PMS, since the arrival directions of aircraft differ, each aircraft can be affected by the wind to a varying degree. In the experiments performed in the EEC, it was stated that the use of the P-PMS is still viable, but it is more difficult to operate than a single PMS, especially when the wind is perpendicular to the sequencing legs. In such a structure it becomes difficult for controllers to organize an efficient and systematic sequence, particularly in busy traffic. In addition, it is essential to achieve the highest efficiency from parallel runways by reassigning arrival and departure aircraft to the runways at large airports operating with multiple parallel runways and P-PMS. However, at such airports, the taxi time of an aircraft assigned to a different runway may increase significantly, which can lead to significant additional costs and passenger dissatisfaction. Although wind uncertainty and the differentiation of the taxi times of aircraft are important factors that can affect capacity and delays, these factors have not been considered in most studies that look to optimize sequences and schedules in PMS. In this study, deterministic and stochastic single and multi-objective mathematical models have been developed to analyze the runway scheduling problem in airports using parallel runways and P-PMS. Wind uncertainties and taxi times are considered alongside the objectives of minimizing total fuel consumption, total flight time, and total delays. As a result, this study reveals how wind and taxi times affect fuel consumption, flight times, delays, and runway preferences, and insights are provided for decision-makers.