Air Traffic Control Capacity Planning Under Demand and Capacity Provision Uncertainty

Stefano Starita (), Arne K. Strauss (), Xin Fei (), Radosav Jovanović (), Nikola Ivanov (), Goran Pavlović () and Frank Fichert ()
Additional contact information
Stefano Starita: Sasin School of Management, Chulalongkorn University, Bangkok 10330, Thailand;
Arne K. Strauss: WHU–Otto Beisheim School of Management, 56179 Vallendar, Germany;
Xin Fei: Warwick Business School, University of Warwick, Coventry CV4 7AL, United Kingdom;
Radosav Jovanović: Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia;
Nikola Ivanov: Faculty of Transport and Traffic Engineering, University of Belgrade, 11000 Belgrade, Serbia;
Goran Pavlović: 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

Transportation Science, 2020, vol. 54, issue 4, 882-896

Abstract: In air traffic management, a fundamental decision with large cost implications is the planning of future capacity provision. Here, capacity refers to the available man-hours of air traffic controllers to monitor traffic. Airspace can be partitioned in various ways into a collection of sectors, and each sector has a fixed maximum number of flights that may enter within a given time period. Each sector also requires a fixed number of man-hours to be operated; we refer to them as sector-hours. Capacity planning usually takes place a long time ahead of the day of operation to ensure that sufficiently many air traffic controllers are available to manage the flow of aircrafts. However, at the time of planning, there is considerable uncertainty regarding the number and spatiotemporal distribution of nonscheduled flights and capacity provision, the former mainly due to business aviation, and the latter usually stemming from the impact of weather, military use of airspaces, etc. Once the capacity decision has been made (in terms of committing to a budget of sector-hours per airspace to represent long-term staff scheduling), on the day of operation, we can influence traffic by enforcing rerouting and tactical delays. Furthermore, we can modify which sectors to open at a given time (the so-called sector-opening scheme) subject to the fixed capacity budgets in each airspace. The fundamental trade-off is between reducing the capacity provision cost at the expense of potentially increasing displacement cost arising from rerouting or delays. To tackle this, we propose a scalable decomposition approach that exploits the structure of the problem and can take traffic and capacity provision uncertainty into account by working with a large number of traffic scenarios. We propose several decision policies based on the resulting pool of solutions and test them numerically using real-world data.

Keywords: air transportation; capacity ordering policies; integer programming applications; decomposition methods (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:inm:ortrsc:v:54:y:2020:i:4:p:882-896

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