Airline scheduling to minimize operational costs and variability

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buir.advisorAktürk, M. Selim
dc.contributor.authorŞimşek, Deniz
dc.date.accessioned2021-08-19T11:00:15Z
dc.date.available2021-08-19T11:00:15Z
dc.date.copyright2021-08
dc.date.issued2021-08
dc.date.submitted2021-08-17
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Master's): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2021.en_US
dc.descriptionIncludes bibliographical references (leaves 97-102).en_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 variabilities from the average in our second objective to generate balanced schedules in terms of resilience. We follow an ε-constraint approach to scalarize and solve our problem via commercial solvers and we also devise a discretized approximation and search algorithm to solve large instances. We compare the recovery performances of our proposed schedules to the minimum cost schedules by a scenario-based posterior analysis. As a key contribution, we show that in the schedule generation phase, designing resilient schedules by allowing them to deviate from the minimum cost within the trade-off between the operational costs and the variability, the potential recovery costs in case of unexpected disruptions can be reduced significantly.en_US
dc.description.degreeM.S.en_US
dc.description.statementofresponsibilityby Deniz Şimşeken_US
dc.format.extentxiv, 125 leaves : charts ; 30 cm.en_US
dc.identifier.itemidB129046
dc.identifier.urihttp://hdl.handle.net/11693/76467
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_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.titleAirline scheduling to minimize operational costs and variabilityen_US
dc.title.alternativeOperasyonal maliyetleri ve değişkenliği enazlayan havayolu çizelgelemeen_US
dc.typeThesisen_US
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