Multiobjective optimization of airline crew management with a genetic algorithm
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Author (Corporation)
Publication date
2023
Typ of student thesis
Course of study
Collections
Type
04B - Conference paper
Editor (Corporation)
Supervisor
Parent work
Innovations in Bio-Inspired Computing and Applications. Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022) Held During December 15-17, 2022
Special issue
DOI of the original publication
Series
Lecture Notes in Networks and Systems
Series number
Volume
Issue / Number
Pages / Duration
109-119
Patent number
Publisher / Publishing institution
Springer
Place of publication / Event location
Cham
Edition
Version
Programming language
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Practice partner / Client
Abstract
In this paper we discuss the real-world problem of crew management in the airline business. We focus on modeling the optimization of the crew rostering, taking into account the constraints from the European Union Aviation Safety Agency (EASA) regulating the flight time limitations (FTL). Special emphasis is put on the preferences and fairness among the crew members. This results in a multiobjective constrained optimization problem, which we solve with a Genetic Algorithm (GA). The fitness function is composed of multiple objectives for which the user can adjust their relative weights, depending on their preferences. The main contribution of the paper is the novel multiobjective problem formulation and its proof-of-concept solution by a GA.
Keywords
Subject (DDC)
Event
13th International Conference on Innovations in Bio-Inspired Computing and Applications
Exhibition start date
Exhibition end date
Conference start date
15.12.2022
Conference end date
17.12.2022
Date of the last check
ISBN
978-3-031-27498-5
978-3-031-27499-2
978-3-031-27499-2
ISSN
Language
English
Created during FHNW affiliation
Yes
Strategic action fields FHNW
Publication status
Published
Review
Peer review of the complete publication
Open access category
Closed
License
Citation
Crego, A., Hanne, T., & Dornberger, R. (2023). Multiobjective optimization of airline crew management with a genetic algorithm. In A. Abraham, A. Bajaj, N. Gandhi, A. M. Madureira, & C. Kahraman (Eds.), Innovations in Bio-Inspired Computing and Applications. Proceedings of the 13th International Conference on Innovations in Bio-Inspired Computing and Applications (IBICA 2022) Held During December 15-17, 2022 (pp. 109–119). Springer. https://doi.org/10.1007/978-3-031-27499-2_10