Traditionally airport systems have been studied using an approach in which the different elements of the system are studied independently. Until recently scientific community has put attention in developing models and techniques that study the system using holistic approaches for understanding cause and effect relationships of the integral system. This chapter presents a case of an airport in which the authors have implemented an approach for improving the turnaround time of the operation. The novelty of the approach is that it uses a combination of simulation, parameter analysis and optimization for getting to the best amount of vehicles that minimize the turnaround time of the airport under study. In addition, the simulation model is such that it includes the most important elements within the aviation system, such as terminal manoeuvring area, runway, taxi networks, and ground handling operation. The results show clearly that the approach is suitable for a complex system in which the amount of variables makes it intractable for getting good solutions in reasonable time.
This work proposes a methodology for developing an airport arrival and departure manager tool. This methodology employs optimization together with simulation techniques for improving the robustness of the solution. An arrival and departure manager tool is intended to help air traffic controllers in managing the inbound and outbound traffic without incurring in conflicts or delays. In this context, air traffic controllers need to have a tool able to help them to make the right decisions in a short time horizon. The main decisions taken in the present methodology for each aircraft are: entry time and entry speed in the airspace and push back time at the gate. The objective of this methodology is to have a smooth flow of aircraft both in the airspace and on the ground. Preliminary tests were made using Paris Charles de Gaulle Airport as case study, and the results show that conflicts were sensibly reduced.
In this paper is presented a methodology that uses simulation together with optimization techniques for a conflict detection and resolution at airports. This approach provides more robust solutions to operative problems, since, optimization allows to come up with optimal or suboptimal solutions, on the other hand, simulation allows to take into account other aspects as stochasticity and interactions inside the system. Both the airport airspace (terminal manoeuvring area), and airside (runway taxiways and terminals), were modelled. In this framework, different restrictions such as speed, separation minima between aircraft, and capacity of airside components were taken into account. The airspace was modeled as a network of links and nodes representing the different routes, while the airside was modeled in a low detail, where runway, taxiways and terminals were modeled as servers with a specific capacity. The objective of this work is to detect and resolve conflicts both in the airspace and in the airside and have a balanced traffic load on the ground.
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