Towards a Heuristic Optimizer for a Target Time Management System in Air Traffic Flow Management

Abstract In Air Traffic Flow Management (ATFM), flights are issued arrival times during unexpected events, such as adverse weather conditions, in order to ensure smooth and safe airport operations. These target times are traditionally allocated on a first-planned, first-served basis, which often leads to inefficiencies due to the different delay costs of individual flights. The HARMONIsed network through smart technology and Collaboration (HARMONIC) project, funded by the Single European Sky ATM Research (SESAR) Joint Undertaking within the EU Horizon Europe program, therefore, explores a collaborative optimization platform to enable flight prioritization across airspace users. In this paper, we describe initial results of the development and validation of a Target-Time Management System (TTMS) in the HARMONIC project. In particular, we present different architecture options, one assuming a trusted platform provider, another option for the assumption of an honest-but-curious platform provider, using secure multi-party computation to protect the private inputs. We also present experimental results for a genetic algorithm for the optimization of assignment of target times to flights.

Keywords: flight prioritization, multi-party computation, evolutionary algorithm, heuristic optimization