Nowadays the main airports throughout the world are suffering because their capacity are getting close to saturation due to the air traffic which is still increasing besides the economic crisis and oil prices. In addition, the forecasts predict an increase in air traffic of at least 3.6% until 2020. This situation makes very important to come up with solutions to alleviate capacity congestions in the main airports throughout the world. Capacity has been perceived traditionally as the factor to be addressed in airport systems and it is faced through a technical perspective. In this paper we propose to change the mind-set and view capacity of airport systems taking other factors than pure technical ones. The discussion is illustrated with the example of Schiphol Airport.
MULTIFILE
Airport management is often challenged by the task of managing aircraft parking positions most efficiently while complying with environmental regulations and capacity restrictions. Frequently this task is additionally affected by various perturbations, affecting punctuality of airport operations. This paper presents an innovative approach for obtaining an efficient stand assignment considering the stochastic nature of the airport environment and emissions reduction target of the modern air transportation industry. Furthermore, the presented methodology demonstrates how the same procedure of creating a stand assignment can help to identify an emissions mitigation potential. This paper illustrates the application of the presented methodology combined with simulation and demonstrates the impact of the application of Bayesian modeling and metaheuristic optimization for reduction of taxi-related emissions.
DOCUMENT
This paper presents an innovative approach that combines optimization and simulation techniques for solving scheduling problems under uncertainty. We introduce an Opt–Sim closed-loop feedback framework (Opt–Sim) based on a sliding-window method, where a simulation model is used for evaluating the optimized solution with inherent uncertainties for scheduling activities. The specific problem tackled in this paper, refers to the airport capacity management under uncertainty, and the Opt–Sim framework is applied to a real case study (Paris Charles de Gaulle Airport, France). Different implementations of the Opt–Sim framework were tested based on: parameters for driving the Opt–Sim algorithmic framework and parameters for riving the optimization search algorithm. Results show that, by applying the Opt–Sim framework, potential aircraft conflicts could be reduced up to 57% over the non-optimized scenario. The proposed optimization framework is general enough so that different optimization resolution methods and simulation paradigms can be implemented for solving scheduling problems in several other fields.
DOCUMENT
