Coping with Uncertainties in Predicting the Aircraft Turnaround Time at Airports

Ehsan Asadi (), Jan Evler, Henning Preis and Hartmut Fricke
Additional contact information
Ehsan Asadi: Institute of Logistics and Aviation, Technische Universität Dresden
Jan Evler: Institute of Logistics and Aviation, Technische Universität Dresden
Henning Preis: Institute of Logistics and Aviation, Technische Universität Dresden
Hartmut Fricke: Institute of Logistics and Aviation, Technische Universität Dresden

A chapter in Operations Research Proceedings 2019, 2020, pp 773-780 from Springer

Abstract: Abstract Predicting the target time of an aircraft turnaround is of major importance for the tactical control of airport and airline network operations. Nevertheless, this turnaround time is subject to many random influences, such as passenger behavior while boarding, resource availability, and short-noticed maintenance activities. This paper proposes a mathematical optimization model for the aircraft turnaround problem while considering various uncertainties along the process. The proposed method is acting on a microscopic, thus detailed operational level. Dealing with uncertainties is implemented by two approaches. First, an analytical procedure based on convolution, which has not been considered in the literature so far but provides fast computational results, is proposed to estimate the turnaround finalization, called Estimated Off-Block Time (EOBT). The convolution algorithm considers all process-related stochastic influences and calculates the probability that a turnaround can be completed within the pre-set target time TOBT. At busy airports, such assessments are needed in order to comply with installed slot allocation mechanisms. Since aircraft turnaround operations reflect a scheduling problem, a chance-constrained MIP programming model is applied as a second approach. This procedure assumes stochastic process durations to determine the best alternative of variable process executions, so that the TOBT can be met. The procedure is applied to an Airbus A320 turnaround.

Keywords: Aircraft turnaround; Analytical convolution; Chance-constrained MIP (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-030-48439-2_94

Ordering information: This item can be ordered from
http://www.springer.com/9783030484392

DOI: 10.1007/978-3-030-48439-2_94

Access Statistics for this chapter

More chapters in Operations Research Proceedings from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().