The following paper presents an innovative approach for dealing with complex capacity problems in aviation. We introduce a sliding window framework composed by an optimization method with a simulation component. By applying this framework in diverse problems that are dependent on time it is possible to find feasible and close-to-reality solutions in shorter time than the ones that could be achieved by evaluating the problem in the complete time-horizon. The framework can be applied to solve diverse problems in aviation or similar industries. We exemplify the approach with a model of Paris Charles de Gaulle Airport in France.
MULTIFILE
KLM is downsizing the full-freight cargo fleet in Schiphol Airport, for that reason it is important for the company and the airport to explore the consequences of moving the cargo transported by the full freighters into the bellies of the passenger flights. The consequences of this action in terms of capacity and requirements are still unknown. The current study illustrates how to analyse the uncertainty present in the system for identifying the limitations and potential consequences of the reduction of full freighter fleet. The options we identify for coping with the current demand is by adjusting their load factors or increase the number of flights. The current model includes the airside operation of the airport, the truck movements and the traffic that arrives at Schiphol which allows addressing the impact of uncertainties of the operation as well as the limitations and potential problems of the phasing-out action.
