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Optimization of staffing strategies at Brussels Airport: a crowd modelling approach

Luyckx, Matthieu
(2024)

Files

Luyckx_81862100_2024.pdf
  • UCLouvain restricted access
  • Adobe PDF
  • 2.42 MB

Details

Supervisors
Delvenne, Jean-Charles ; Krings, Gautier
Faculty
Ecole polytechnique de Louvain
Degree label
Master [120] en science des données, orientation technologies de l'information, à finalité spécialisée
Abstract
Finding a balance between passengers satisfaction, crowd management and reduction of costs is one of the goals of Brussels Airport. To this end, we will explore through crowd modelling the possibilities of reducing the workforce while ensuring the correct flow of passengers through the airport network’s multiple queues. Focusing on the simulation of the crowds, this thesis aims to understand the underlying concepts of queuing theory before finding a way to minimize the workforce needed to ensure both passengers satisfaction and reduction of costs. Assigning enough servers to handle the unstable passenger throughput while trying to minimize them can be a rough task. However, considering all situations that could happen without knowing the exact arrival times of passengers is even harder. These are examples of the problems we are about to face, and many techniques will be introduced to make sure we represent correctly the field reality. Black-box optimization techniques, M/M/c queuing modelling, Gillespie algorithm or Monte Carlo method are some of the concepts that will be used and described in this work for providing Brussels Airport the results they need.