2024-03-28T23:46:15Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/69772022-11-04T14:12:55Zcom_10259.4_104com_10259_2604col_10259_6848
Repositorio Institucional de la Universidad de Burgos
author
Fuentes, Manuel
author
Cadarso, Luis
author
Vaze, Vikrant
author
Barnhart, Cynthia
2022-09-21T10:10:11Z
2022-09-21T10:10:11Z
2021-07
978-84-18465-12-3
http://hdl.handle.net/10259/6977
10.36443/10259/6977
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.
eng
PlanificaciĆ³n del transporte
Industria aƩrea
Planning of transport
Airline industry
A novel approach to the tail assignment problem in airline planning
info:eu-repo/semantics/conferenceObject
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URL
https://riubu.ubu.es/bitstream/10259/6977/1/Fuentes_CIT2021_2309-2320.pdf
File
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191172
application/pdf
Fuentes_CIT2021_2309-2320.pdf