Constraint-based robust planning and scheduling of airport apron operations through simheuristics

Yagmur S. Gök (), Silvia Padrón (), Maurizio Tomasella (), Daniel Guimarans and Cemalettin Ozturk ()
Additional contact information
Yagmur S. Gök: University of Edinburgh
Silvia Padrón: TBS Education
Maurizio Tomasella: University of Edinburgh
Daniel Guimarans: Amazon
Cemalettin Ozturk: Process, Energy and Transport Engineering

Annals of Operations Research, 2023, vol. 320, issue 2, No 11, 795-830

Abstract: Abstract Scheduling aircraft turnarounds at airports requires the coordination of several organizations, including the airport operator, airlines, and ground service providers. The latter manage the necessary supplies and teams to handle aircraft in between consecutive flights, in an area called the airport ‘apron’. Divergence and conflicting priorities across organizational borders negatively impact the smooth running of operations, and play a major role in departure delays. We provide a novel simulation-optimization approach that allows multiple service providers to build robust plans for their teams independently, whilst supporting overall coordination through central scheduling of all the involved turnaround activities. Simulation is integrated within the optimization process, following simheuristic techniques, which are augmented with an efficient search driving mechanism. Two tailored constraint-based feedback routines are automatically generated from simulation outputs to constrain the search space to solutions more likely to ensure plan robustness. The two simulation components provide constructive feedback on individual routing problems and global turnaround scheduling, respectively. Compared to the state-of-the-art approach for aircraft turnaround scheduling and routing of service teams, our methodology improves the apron’s on-time punctuality, without the need for the involved organizations to share sensitive information. This supports a wider applicability of our approach in a multiple-stakeholder environment.

Keywords: Simheuristics; Simulation; Optimization; Large neighborhood search; Robust scheduling; Constraint programming (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10479-022-04547-0

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