DEMAND CAPACITY BALANCING IN MULTI-MODAL TRANSPORTATION THROUGH OPTIMIZATION AND SIMULATION

Abstract : The current Air traffic System in Europe relies on airspace and airport capacity estimates computed by the Air National Service Providers (ANSPs) using demand forecast and Air traffic Controllers operations schedules. The Demand Capacity Balancing (DCB) aims at reducing the Air Traffic Management resources held in reserve to cope with demand peaks by providing the system with demand smoothing means. A recent study on the subject suggests introducing a congestion-based route fee that encourages users to avoid crowded slots for a given departure and arrival airport [1]. An optimal equilibrium point can then be reached through a clever choice of penalties incurred by flying at departure times adversely impacting congestion. Alternative routes may also be considered in the planning, as for a whole category of customers price tag is more important than travel time. However, taking into account that for short haul flights alternative means of transportation may be a viable option, DCB can be addressed in a wider scope by considering surface vehicles along aircraft. A side effect of this holistic approach is the ability to cope with disruptive events. The present work describes a simulation and optimization model tailored to this particular problem.
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Submitted on : Monday, November 4, 2019 - 12:11:21 PM
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Georges Mykoniatis, Stéphane Puechmorel, Felix Moracamino, Leila Zerrouki, Marcel Richard. DEMAND CAPACITY BALANCING IN MULTI-MODAL TRANSPORTATION THROUGH OPTIMIZATION AND SIMULATION. IC-EPSMSO 2019, LFME, Jul 2019, Athens, Greece. ⟨hal-02344784⟩

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