Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
ATC work shift scheduling using multistart simulated annealing and regular expressions
Year:2017
Research Areas
  • Non linear programming,
  • Multiple objectives,
  • Air traffic control,
  • Air traffic management
Information
Abstract
In this paper, we propose a new approach for solving the air traffic controller (ATC) work shift scheduling problem, which minimizes the number of ATCs required to cover a given airspace sectoring, while satisfying a set of ATC labor conditions. This optimization problem belongs to the class of timetabling problems. The size and complexity of these combinatorial problems make them hard or even impossible to solve with exact methods. In the proposed approach, initial feasible solutions are first built using a heuristic based on optimized templates, and then multistart simulated annealing is used to reach optimal solutions. In the search process, we use regular expressions to check the feasibility of the generated solutions. This provides high testing speed and modularity for a clear and maintainable implementation of the optimization model. Once the optimal ATC number is reached in one or more solutions, they are used as the initial solutions for a new optimization process aimed at balancing the ATC workloads. The proposed approach is illustrated using a real example, and the optimal solution reached outperforms the reference solution, i.e. a real solution derived from the currently used tools based on templates. Indeed, one less ATC is needed to cover the airspace sectoring, and the ATC workloads are more balanced.
International
Si
Congress
EWG-DSS 2017 International Conference on Decision Support System Technology
960
Place
Namur, Bélgica
Reviewers
Si
ISBN/ISSN
978-2-917490-28-0
Start Date
29/05/2017
End Date
31/05/2017
From page
169
To page
175
Proceedings of the EWG-DSS 2017 International Conference on Decision Support System Technology
Participants
  • Autor: Faustino Tello Caballo (UPM)
  • Autor: Alfonso Mateos Caballero (UPM)
  • Autor: Antonio Jimenez Martin (UPM)
  • Autor: Juan Antonio Fdez del Pozo De Salamanca (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de análisis de decisiones y estadística
  • Grupo de Investigación: Computational Intelligence Group
  • Departamento: Inteligencia Artificial
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
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