Exploring Future UDPP Concepts through Computational Behavioural Economics

This paper presents an agent-based modelling (ABM) approach aimed at enabling a rigorous and comprehensive study of flight prioritization mechanisms in the context of demand and capacity imbalances. The implemented model adopts the paradigm of agent-based computational economics, as a particularly suitable framework for the representation of features that are not properly captured by classical approaches, such as bounded rationality or hyperbolic discounting. The main components are described, including a simplified network environment, the agents, the applied behavioral rules and the included prioritization mechanisms: SFP, E-SFP and slot auctioning. Finally, a comparative performance analysis of the prioritization concepts is presented, evaluating their impact on punctuality, cost-efficiency, equity and robustness in the presence of non-rational behaviors. Results show how SFP, counterintuitively, worsens the baseline performance in some scenarios, due to unexpected network effects, while the slot auctioning concept provides the best performance. In general, behavioral biases worsen performance of the mechanisms; however, the auction mechanism results are not significantly affected by the modelled behavioral biases.