Multiobjective optimization of airline crew management with a genetic algorithm

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

Themenheft

Reihe / Serie

Lecture Notes in Networks and Systems

Reihennummer

Jahrgang / Band

Ausgabe / Nummer

Seiten / Dauer

109-119

Patentnummer

Verlag / Herausgebende Institution

Springer

Verlagsort / Veranstaltungsort

Cham

Auflage

Version

Programmiersprache

Abtretungsempfänger:in

Praxispartner:in/Auftraggeber:in

Zusammenfassung

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.

Schlagwörter

Fachgebiet (DDC)

330 - Wirtschaft

Projekt

Veranstaltung

13th International Conference on Innovations in Bio-Inspired Computing and Applications

Startdatum der Ausstellung

Enddatum der Ausstellung

Startdatum der Konferenz

15.12.2022

Enddatum der Konferenz

17.12.2022

Datum der letzten Prüfung

ISBN

978-3-031-27498-5
978-3-031-27499-2

ISSN

Sprache

Englisch

Während FHNW Zugehörigkeit erstellt

Ja

Zukunftsfelder FHNW

Publikationsstatus

Veröffentlicht

Begutachtung

Peer-Review der ganzen Publikation

Open Access-Status

Closed

Lizenz

Zitation

CREGO, Alfredo, Thomas HANNE und Rolf DORNBERGER, 2023. Multiobjective optimization of airline crew management with a genetic algorithm. In: Ajith ABRAHAM, Anu BAJAJ, Niketa GANDHI, Ana Maria MADUREIRA und Cengiz KAHRAMAN (Hrsg.), 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. Cham: Springer. 2023. S. 109–119. Lecture Notes in Networks and Systems. ISBN 978-3-031-27498-5. Verfügbar unter: https://irf.fhnw.ch/handle/11654/48187

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