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An Analytical Approach for Optimal Resilience Management in Future ATM Systems

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 616))

Abstract

The air transportation system is a large-scale socio-technical system and its modelling approaches emphasize the sociological dimension due to the increasing importance of collaborative decision-making processes in the future Air Traffic Management (ATM). Resilience is assuming an increasing importance within ATM, but it is difficult or even impossible to establish the resilience role in realizing the targeted performance levels of an air traffic system. This paper proposes a systematic methodology for resilience management in ATM. It introduces an analytical definition of a resilience metric for an ATM system and formally states the resilience management problem as an optimization problem. Moreover, it describes a strategy for the problem solution and provides some preliminary results in order to quantitatively prove the validity of the methodology.

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Acknowledgments

This work is co-financed by EUROCONTROL acting on behalf of the SESAR Joint Undertaking and the European Union as part of Work Package E in the SESAR Programme. Opinions expressed in this work reflect the authors’ views only and EUROCONTROL and/or the SJU shall not be considered liable for them or for any use that may be made of the information contained herein.

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Correspondence to Domenico Pascarella .

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© 2016 Springer International Publishing Switzerland

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Pascarella, D., Gargiulo, F., Errico, A., Filippone, E. (2016). An Analytical Approach for Optimal Resilience Management in Future ATM Systems. In: Novais, P., Camacho, D., Analide, C., El Fallah Seghrouchni, A., Badica, C. (eds) Intelligent Distributed Computing IX. Studies in Computational Intelligence, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-25017-5_39

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  • DOI: https://doi.org/10.1007/978-3-319-25017-5_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25015-1

  • Online ISBN: 978-3-319-25017-5

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