dc.contributor.author | Fuentes, Manuel | |
dc.contributor.author | Cadarso, Luis | |
dc.contributor.author | Vaze, Vikrant | |
dc.contributor.author | Barnhart, Cynthia | |
dc.date.accessioned | 2022-09-21T10:10:11Z | |
dc.date.available | 2022-09-21T10:10:11Z | |
dc.date.issued | 2021-07 | |
dc.identifier.isbn | 978-84-18465-12-3 | |
dc.identifier.uri | http://hdl.handle.net/10259/6977 | |
dc.description | Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos | es |
dc.description.abstract | Combinatorial optimization problems abound in the field of airline planning. Aircraft and
passengers fly on networks made up of flights and airports. To schedule aircraft, assignments
of fleet types to flights and of aircraft to routes must be determined. The former is known as
the fleet assignment problem while the latter is known as the aircraft routing problem in the
literature. Aircraft routing is typically addressed as a feasibility problem, the solution to
which is required for the construction of crew schedules. All these issues are typically
resolved 4 to 6 months before the day of operations. As a result, there is little information
available about each aircraft's operational status when making such decisions. The tail
assignment problem, which has received little attention in the literature, is solved when
additional information about operational conditions is revealed, with the goal of determining
each aircraft's route for the day of operations while accounting for the originally planned
aircraft routes and crew schedules. As a result, it is a problem that must be resolved closer
to the day of operations. We propose a mathematical programming approach based on
sequencing that captures all operational constraints and maintenance requirements while
minimizing operational costs and schedule changes relative to original plans. The
computational experiments are based on realistic cases drawn from a Spanish airline with
over 1000 flights and over 100 aircraft. | en |
dc.description.sponsorship | This research was supported by Project Grants TRA2016-76914-C3-3-P by the Ministerio de Economía y Competitividad, Spain, and CAS19/00036 by the Ministerio de Ciencia, Innovación y Universidades, Spain. | en |
dc.format.mimetype | application/pdf | |
dc.language.iso | eng | es |
dc.publisher | Universidad de Burgos. Servicio de Publicaciones e Imagen Institucional | es |
dc.relation.ispartof | R-Evolucionando el transporte | es |
dc.relation.uri | http://hdl.handle.net/10259/6490 | |
dc.subject | Planificación del transporte | es |
dc.subject | Planning of transport | en |
dc.subject | Industria aérea | es |
dc.subject | Airline industry | en |
dc.subject.other | Ingeniería civil | es |
dc.subject.other | Civil engineering | en |
dc.subject.other | Transportes | es |
dc.subject.other | Transportation | en |
dc.subject.other | Tecnología | es |
dc.subject.other | Technology | en |
dc.title | A novel approach to the tail assignment problem in airline planning | en |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.relation.publisherversion | https://doi.org/10.36443/9788418465123 | es |
dc.identifier.doi | 10.36443/10259/6977 | |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TRA2016-76914-C3-3-P/ES/ROBUSTEZ, EFICIENCIA Y RECUPERACION DE SISTEMAS DE TRANSPORTE PUBLICO | es |
dc.relation.projectID | info:eu-repo/grantAgreement/MICIU/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/CAS19%2F00036 | |
dc.page.initial | 2309 | es |
dc.page.final | 2320 | es |
dc.type.hasVersion | info:eu-repo/semantics/publishedVersion | es |