IDEAS home Printed from https://ideas.repec.org/a/inm/ortrsc/v57y2023i4p999-1018.html
   My bibliography  Save this article

Cross-Border Capacity Planning in Air Traffic Management Under Uncertainty

Author

Listed:
  • Jan-Rasmus Künnen

    (Demand Management and Sustainable Transport, WHU–Otto Beisheim School of Management, 56179 Vallendar, Germany)

  • Arne K. Strauss

    (Demand Management and Sustainable Transport, WHU–Otto Beisheim School of Management, 56179 Vallendar, Germany)

  • Nikola Ivanov

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia)

  • Radosav Jovanović

    (Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia)

  • Frank Fichert

    (Faculty of Tourism and Transport, Worms University of Applied Sciences, 67549 Worms, Germany)

  • Stefano Starita

    (Sasin School of Management, Chulalongkorn University, 10330 Bangkok, Thailand)

Abstract

In European air traffic management (ATM), it is an important decision how much capacity to provide for each airspace, and it has to be made weeks or even months in advance of the day of operation. Given the uncertainty in demand that may materialize until then along with variability in capacity provision (e.g., due to weather), Airspace Users could face high costs of displacements (i.e., delays and reroutings) if capacity is not provided where and when needed. We propose a new capacity sharing scheme in which some proportion of overall capacities can be flexibly deployed in any of the airspaces of the same alliance (at an increased unit cost). This allows us to hedge against the risk of capacity underprovision. Given this scheme, we seek to determine the optimum budget for capacities provided both locally and in cross-border sharing that results in the lowest expected network costs (i.e., capacity and displacement costs). To determine optimum capacity levels, we need to solve a two-stage newsvendor problem: We first decide on capacities to be provided for each airspace, and after uncertain demand and capacity provision disruptions have materialized, we need to decide on the routings of flights (including delays) as well as the sector opening scheme of each airspace to minimize costs. We propose a simulation optimization approach for searching the most cost-efficient capacity levels (in the first stage), and a heuristic to solve the routing and sector opening problem (in the second stage), which is N P -hard. We test our approach in a large-sized simulation study based on real data covering around 3,000 flights across Western European airspace. We find that our stochastic approach significantly reduces network costs against a deterministic benchmark while using less computational resources. Experiments on different setups for capacity sharing show that total variable costs can be reduced by more than 8% if capacity is shared across borders: even though we require that no airspace can operate lower capacities under capacity sharing than without (this is to avoid substitution of expensive air traffic controllers with those in countries with a lower wage level). We also find that the use of different technology providers is a major obstacle to reap the benefits from capacity sharing and that sharing capacities across airspaces of the same country may instead be preferred.

Suggested Citation

  • Jan-Rasmus Künnen & Arne K. Strauss & Nikola Ivanov & Radosav Jovanović & Frank Fichert & Stefano Starita, 2023. "Cross-Border Capacity Planning in Air Traffic Management Under Uncertainty," Transportation Science, INFORMS, vol. 57(4), pages 999-1018, July.
  • Handle: RePEc:inm:ortrsc:v:57:y:2023:i:4:p:999-1018
    DOI: 10.1287/trsc.2023.1210
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/trsc.2023.1210
    Download Restriction: no

    File URL: https://libkey.io/10.1287/trsc.2023.1210?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ortrsc:v:57:y:2023:i:4:p:999-1018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.