Runway assignment optimisation model for Istanbul Airport considering multiple parallel runway operations
AERONAUTICAL JOURNAL, vol.128, no.1330, pp.2799-2814, 2024 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 128 Issue: 1330
- Publication Date: 2024
- Doi Number: 10.1017/aer.2024.60
- Journal Name: AERONAUTICAL JOURNAL
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC
- Page Numbers: pp.2799-2814
- Keywords: air traffic management, mixed integer linear programming, multiple parallel runways, runway assignment optimisation, taxi operation
- Eskisehir Osmangazi University Affiliated: Yes
Abstract
The aviation industry has rapidly developed in recent years. Due to the increased number of flight operations, managing air traffic has become essential. The air traffic management system aims to reduce the air traffic control workload and use existing resources more efficiently. This study proposed a new mixed integer linear programming model to minimise the total fuel consumption during taxi operations for the runway assignment problem, comparing the actual Istanbul Airport runway assignment data. The average taxi times are calculated using the 30,000-flight operations data for each arrival and departure taxi route. Also, 47 different aircraft types are obtained using the data for the fuel consumption calculation. The International Civil. Aviation Organisation (IACO) aircraft engine emissions databank provides the fuel consumption values for each aircraft according to engine type. This approach allows our model to calculate more realistic fuel consumption for taxi operations, as each aircraft engine type has a different fuel consumption value. The proposed model is implemented at Istanbul Airport, the busiest airport in Turkey, where multiple parallel runway operations are applied. The results showed that the proposed model reduced total fuel consumption for taxi operations between 6.6% and 14.4% compared to the actual Istanbul Airport runway assignment data.