Highlights Simulation-optimisation approach generates less pollutant stand allocation. Divide-and-conquer approach identifies efficient solution regions. The manual intervention with the algorithm enables to get more efficient solutions. Simulation introduces variability of the real system in the solutions. Bayesian modelling introduces deviation probabilities in the algorithm.
Abstract Modern airport management is challenged by the task of operating aircraft parking positions most efficiently while complying with environmental policies, restrictions, schedule disruptions, and capacity limitations. This study proposes a novel framework for the stand allocation problem that uses a divide-and-conquer approach in combination with Bayesian modelling, simulation, and optimisation to produce less-pollutant solutions under realistic conditions. The framework presents three innovative aspects. First, inputs from the stochastic analysis module are used in a multivariate optimisation for generating variability-robust solutions. Second, a combination of optimisation and simulation is used to finely explore the impact of realistic uncertainty uncaptured by the framework. Lastly, the framework considers the role of human beings as the final control of operational conditions. A case study is presented as a proof of concept and demonstrates results achievable and benefits of the framework proposed. The experimental results demonstrate that the framework generates less-pollutant solutions under realistic conditions.
Reducing airport environmental footprint using a disruption-aware stand assignment approach
2020-01-01
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Airport stand assignment model
TIBKAT | 1990
|Airport stand assignment model (final report)
TIBKAT | 1991
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