Multi-airport system flight slot optimization method based on absolute fairness

Yafei Li; Yuxi Liu; Yafei Li; Yuxi Liu

doi:10.3934/mbe.2023797

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 10: 17919-17948. doi: 10.3934/mbe.2023797

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Research article

Multi-airport system flight slot optimization method based on absolute fairness

Yafei Li ^,,
Yuxi Liu

School of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China

Received: 30 July 2023 Revised: 11 September 2023 Accepted: 13 September 2023 Published: 19 September 2023

With the rapid development of the civil aviation industry, the number of flights has increased rapidly. However, the availability of flight slot resources remains limited, and how to allocate flight slot resources effectively has been a hot research topic in recent years. A comprehensive flight slot optimization method can significantly enhance the rationality of the allocation results. The effective allocation of flight slot is the key to improving the operational efficiency of the multi-airport system. We will optimize the flight schedule of the entire multi-airport system considering the fairness of each airport in it. The optimization results will provide an important reference for the reasonable allocation of flight slot within the multi-airport system. Based on the operation characteristics of the multi-airport system, we have established a multi-objective flight slot allocation optimization model. In this model, we set the airport capacity limit, shared waypoint capacity limit and aircraft turnaround time limit as the constraints. The optimization goal of the model is to minimize total flight schedule displacement and the maximum deviation of fairness from the absolute fairness. Gurobi solver is used to solve the model. We have innovatively incorporated the rolling capacity constraint method into our model to ensure more accurate flight slot allocation results. The Beijing-Tianjin-Hebei regional multi-airport system is selected as an example to verify the above model, and the flight slot optimization results have successfully met the fairness goal. The comparative analysis has demonstrated that the rolling capacity constraint method significantly improves the accuracy of solution results, leading to more stable flight slot allocation. The results also prove that the flight slot allocation method of multi-airport system based on absolute fairness of peak demand can improve the fairness of the allocation results. To achieve a higher level of fairness, we have found that the peak-demand based fairness method requires a smaller slot displacement compared to the non-peak demand-based method. Through the optimization of flight slot of the multi-airport system, the coordination between airports can be significantly improved. It can provide a new solution for the efficient operation of the multi-airport system.
- multi-airport system,
- flight slot optimization,
- absolute fairness,
- peak demand,
- rolling constraint
Citation: Yafei Li, Yuxi Liu. Multi-airport system flight slot optimization method based on absolute fairness[J]. Mathematical Biosciences and Engineering, 2023, 20(10): 17919-17948. doi: 10.3934/mbe.2023797

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Abstract

With the rapid development of the civil aviation industry, the number of flights has increased rapidly. However, the availability of flight slot resources remains limited, and how to allocate flight slot resources effectively has been a hot research topic in recent years. A comprehensive flight slot optimization method can significantly enhance the rationality of the allocation results. The effective allocation of flight slot is the key to improving the operational efficiency of the multi-airport system. We will optimize the flight schedule of the entire multi-airport system considering the fairness of each airport in it. The optimization results will provide an important reference for the reasonable allocation of flight slot within the multi-airport system. Based on the operation characteristics of the multi-airport system, we have established a multi-objective flight slot allocation optimization model. In this model, we set the airport capacity limit, shared waypoint capacity limit and aircraft turnaround time limit as the constraints. The optimization goal of the model is to minimize total flight schedule displacement and the maximum deviation of fairness from the absolute fairness. Gurobi solver is used to solve the model. We have innovatively incorporated the rolling capacity constraint method into our model to ensure more accurate flight slot allocation results. The Beijing-Tianjin-Hebei regional multi-airport system is selected as an example to verify the above model, and the flight slot optimization results have successfully met the fairness goal. The comparative analysis has demonstrated that the rolling capacity constraint method significantly improves the accuracy of solution results, leading to more stable flight slot allocation. The results also prove that the flight slot allocation method of multi-airport system based on absolute fairness of peak demand can improve the fairness of the allocation results. To achieve a higher level of fairness, we have found that the peak-demand based fairness method requires a smaller slot displacement compared to the non-peak demand-based method. Through the optimization of flight slot of the multi-airport system, the coordination between airports can be significantly improved. It can provide a new solution for the efficient operation of the multi-airport system.

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