Resilient airline scheduling to minimize delay risks

buir.contributor.authorAktürk, M. Seli̇m
buir.contributor.orcidAktürk, M. Seli̇m|0000-0003-0515-1644
dc.citation.epage103734- 31en_US
dc.citation.spage103734- 1en_US
dc.citation.volumeNumber141en_US
dc.contributor.authorŞi̇mşek, D.
dc.contributor.authorAktürk, M. Seli̇m
dc.date.accessioned2023-02-16T11:25:12Z
dc.date.available2023-02-16T11:25:12Z
dc.date.issued2022-06-06
dc.departmentDepartment of Industrial Engineeringen_US
dc.description.abstractAirlines tend to design their flights schedules with the primary concern of the minimization of operational costs. However, the recently emerging idea of resilient scheduling defined as staying operational in case of unexpected disruptions and adaptability should be of great importance for airlines as well due to the high opportunity costs caused by the flight cancellations and passenger inconvenience caused by delays in the schedule. In this study, we integrate resilient airline schedule design, aircraft routing and fleet assignment problems with uncertain non-cruise times and controllable cruise times. We follow a data-driven method to estimate flight delay probabilities to calculate the airport congestion coefficients required for the probability distributions of non-cruise time random variables. We formulate the problem as a bi-criteria nonlinear mixed integer mathematical model with chance constraints. The nonlinearity caused by the fuel consumption and CO2 emission function associated with the controllable cruise times in our first objective is handled by second order conic inequalities. We minimize the total absolute deviation of the aircraft path variability’s from the average in our second objective to generate balanced schedules in terms of resilience. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis.en_US
dc.description.provenanceSubmitted by Ezgi Uğurlu (ezgi.ugurlu@bilkent.edu.tr) on 2023-02-16T11:25:12Z No. of bitstreams: 1 Resilient_airline_scheduling_to_minimize_delay_risks.pdf: 824758 bytes, checksum: d1653c4e0bdc86e889e2a3d7383ddb93 (MD5)en
dc.description.provenanceMade available in DSpace on 2023-02-16T11:25:12Z (GMT). No. of bitstreams: 1 Resilient_airline_scheduling_to_minimize_delay_risks.pdf: 824758 bytes, checksum: d1653c4e0bdc86e889e2a3d7383ddb93 (MD5) Previous issue date: 2022-06-06en
dc.embargo.release2024-06-06
dc.identifier.doi10.1016/j.trc.2022.103734en_US
dc.identifier.eissn1879-2359
dc.identifier.issn0968-090X
dc.identifier.urihttp://hdl.handle.net/11693/111448
dc.language.isoEnglishen_US
dc.publisherElsevier Ltden_US
dc.relation.isversionofhttps://doi.org/10.1016/j.trc.2022.103734en_US
dc.source.titleTransportation Research Part C: Emerging Technologiesen_US
dc.subjectResilient airline schedulingen_US
dc.subjectAircraft routing and fleetingen_US
dc.subjectCruise time controllabilityen_US
dc.subjectChance constraintsen_US
dc.subjectSecond order cone programmingen_US
dc.titleResilient airline scheduling to minimize delay risksen_US
dc.typeArticleen_US

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