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Optimizing airline crew scheduling using biased randomization: a case study

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dc.contributor.authorAgustín Martín, Alba
dc.contributor.authorGruler, Aljoscha
dc.contributor.authorArmas, Jesica de
dc.contributor.authorJuan, Ángel A.
dc.contributor.departmentEstadística e Investigación Operativaes_ES
dc.contributor.departmentEstatistika eta Ikerketa Operatiboaeu
dc.date.accessioned2023-09-11T10:02:54Z
dc.date.available2023-09-11T10:02:54Z
dc.date.issued2016
dc.date.updated2023-09-11T09:59:45Z
dc.description.abstractVarious complex decision making problems are related to airline planning. In the competitive airline industry, ecient crew scheduling is hereby of major practical importance. This paper presents a metaheuristic approach based on biased randomization to tackle the challenging Crew Pairing Problem (CPP). The objective of the CPP is the establishment of ight pairings allowing for cost minimizing crew- ight assignments. Experiments are done using a real-life case with dierent constraints. The results show that our easy-to-use and fast algorithm reduces overall crew ying times and the necessary number of accompanying crews compared to the pairings currently applied by the company.en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAgustín, A., Gruler, A., De Armas, J., & Juan, A. A. (2016). Optimizing airline crew scheduling using biased randomization: A case study. En O. Luaces, J. A. Gámez, E. Barrenechea, A. Troncoso, M. Galar, H. Quintián, & E. Corchado (Eds.), Advances in Artificial Intelligence (Vol. 9868, pp. 331-340). Springer International Publishing. https://doi.org/10.1007/978-3-319-44636-3_31en
dc.identifier.doi10.1007/978-3-319-44636-3_31
dc.identifier.isbn978-3-319-44635-6
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/46308
dc.language.isoengen
dc.publisherSpringeren
dc.relation.ispartofLuaces, O.; Gámez, J. A.; Barrenechea, E.; Troncoso, A.; Galar, M.; Quintián, H.; Corchado, E. (Eds.). Advances in Artificial Intelligence: 17th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016: proceedings. Berlín: Springer; 2016. p.331-340 978-3-319-44635-6en
dc.relation.publisherversionhttps://doi.org/10.1007/978-3-319-44636-3_31
dc.rights© Springer International Publishing Switzerland 2016en
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.subjectBiased randomizationen
dc.subjectAirline planningen
dc.subjectMetaheuristicsen
dc.subjectCrew pairing problemen
dc.subjectCrew schedulingen
dc.titleOptimizing airline crew scheduling using biased randomization: a case studyen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versionVersión aceptada / Onetsi den bertsioaes
dc.type.versioninfo:eu-repo/semantics/acceptedVersionen
dspace.entity.typePublication
relation.isAuthorOfPublication4fe81952-0641-4201-878d-bfa374ede534
relation.isAuthorOfPublication.latestForDiscovery4fe81952-0641-4201-878d-bfa374ede534

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