Abstract
Serious congestion and delay problems exist in most of the busiest airports worldwide because of imbalance between scarce airport slot resources and increasing traffic demand. Various factors, especially weather conditions, exacerbate the demand–capacity imbalance. This paper presents a robust model for simultaneous slot allocation on an airport network in multiple calendar days, considering airport capacity uncertainty. The idea of robust optimization is conducive to sustainable and stable decision-making. Robustness is represented through reducing the potential scheduling conflicts in the worst case. Then the model links the strategic decisions and pre-tactical decisions in air traffic management (ATM) through the tradeoff between strategic discrepancy cost and operational congestion cost. Under the support of the Cplex solver, numerical analyses are taken to validate the characteristics and effectiveness of the proposed model. The results show that the proposed model effectively eliminates the existing and potential scheduling conflicts, and makes effective tradeoffs between airline preference and potential airport congestion risk.
Highlights
In recent years, rapid growth of air traffic demand brings frequent and serious congestion and delay problems all over the world
We propose a robust optimization model for a network-based strategic slot scheduling problem, which contributes to obtain sustainable
We propose a robust optimization model for a network-based strategic slot scheduling problem, which contributes to obtain sustainable and stable decisions
Summary
Rapid growth of air traffic demand brings frequent and serious congestion and delay problems all over the world. In most practical management or academic researches, the slot allocation problems of the two phases are handled independently This type of processing ignores the reliability and robustness of the initial slot allocation plan, at the same time increases the rescheduling costs of both the airline companies and the traffic management department, and the potential congestion risk. In this work we develop a robust optimization model for a multi-airport multi-calendar day slot allocation problem, which aims to improve decision robustness by linking the decisions of the strategic phase and the pre-tactical phase. This robust optimization idea is a method that meets the sustainability requirements of airports.
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