Öz

This study presents a model that combines aircraft sequencing and passenger transfer dynamics to analyze the transfer process in terms of delay and how air-to-air and air-to-train transfer passengers reach stations and gates. The model considers real-world factors such as distances inside the terminal, walking times depending on baggage and gender, and waiting times at bus/metro stations. The research includes identifying the flights with the highest number of transfer passengers and conducting the analysis by giving priority to the busiest five aircraft. Individual behaviors of passengers, such as baggage and walking times, are also included in the optimization framework. When the differences between the models are analyzed, passengers’ early arrival times at transfer points vary 0-5 minutes. Although this is important, no statistical difference was found. The analysis shows that Model 3 (43%) is superior to the others. While Model 2 reached an average delay of 1,066 seconds, Model 3 produced a delay of 185 seconds. Model 1 and 3 have similar performance. The combination of aircraft sequencing and transfer dynamics is the original contribution of the model. In addition, by including passenger-specific factors and operational constraints in the model, it becomes possible to offer more realistic and practical solutions.

Anahtar Kelimeler

• Transfer passengers
• aircraft sequencing
• passenger dynamics
• passenger flow
• mathematical modelling

Uçuş sıralaması ve yolcu akışı optimizasyonu: İstanbul Sabiha Gökçen Havalimanı

Öz

Bu çalışma, havada bekleme süresi ve hava ve tren aktarma yolcularının istasyon ve kapılara ulaşımı açısından transfer sürecini analiz etmek için uçak sıralaması ile yolcu aktarma dinamiklerini bütünleştiren bir model sunmaktadır. Model, terminal içerisindeki noktalara olan mesafeler, bagaj durumu ve cinsiyete bağlı yürüme süreleri ile otobüs ve metro istasyonlarındaki bekleme süreleri gibi gerçek dünya faktörlerini dikkate almaktadır. Araştırma, en yüksek transfer yolcusuna sahip uçuşların belirlenmesini ve yirmi uçaktan en yoğun beşe öncelik verilerek analiz yapılmasını içermektedir. Yolcuların bagaj ve yürüme süreleri gibi bireysel davranışları da optimizasyon çerçevesine dahil edilmiştir. Modeller arası fark analiz edildiğinde yolcuların transfer noktalarına erken varış süreleri 0-5 dakika arasında değişmektedir. Bu, pratik olarak önemli olsa da modeller arasında anlamlı bir fark tespit edilememiştir. Analiz sonuçları, Model 3’ün (%43) diğer modellere kıyasla daha başarılı olduğunu göstermektedir. Model 2, ortalama 1.066 saniye gecikme sonucuna ulaşırken, Model 3 ise 185 saniye gecikmeye sahip bir çözüm üretmiştir. Bulgular, yolcuların tren istasyonu ve aktarma uçuş kapısına ulaşma sürelerinin iyileştirilmesinde Model 1 ile Model 3’ün benzer bir performans sergilediğini göstermektedir. Literatürde genelde ayrı incelenen uçak sıralama ve yolcu aktarma dinamiklerinin birleşimi, modelin özgün katkısını oluşturmaktadır. Ayrıca, modelde yolcuya özgü faktörler ve operasyonel kısıtlar dahil edilerek daha gerçekçi ve uygulanabilir çözümler sunulması sağlanmıştır.

Anahtar Kelimeler

• Transfer yolcu
• uçak sıralama
• yolcu dinamikleri
• yolcu akışı
• matematiksel modelleme

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