Optimizing airline operations under uncertainty

buir.advisorAktürk, M. Selim
dc.contributor.authorAydıner, Özge Şafak
dc.date.accessioned2019-07-01T06:51:39Z
dc.date.available2019-07-01T06:51:39Z
dc.date.copyright2019-06
dc.date.issued2019-06
dc.date.submitted2019-06-27
dc.departmentDepartment of Industrial Engineeringen_US
dc.descriptionCataloged from PDF version of article.en_US
dc.descriptionThesis (Ph.D.): Bilkent University, Department of Industrial Engineering, İhsan Doğramacı Bilkent University, 2019.en_US
dc.descriptionIncludes bibliographical references (pages 165-176).en_US
dc.description.abstractFluctuations in passenger demand, airport congestion, and high fuel costs are the main threats to airlines' profit, thereby need to be carefully addressed in airline scheduling problems. This study takes an advantage of aircraft cruise speed control in several scheduling problems to keep the cost of fuel manageable. We first generate a flight schedule by integrating strategic departure time decisions, tactical eeting and routing decisions and more operational flight timing decisions under stochastic demand and non-cruise times. Our model differs from the existing studies by including aircraft cruise speed decisions to compensate for increase in non-cruise time variations due to the airport congestion. To e ciently solve the problem, we provide a scenario group-wise decomposition algorithm. Then, we consider a new problem which aims to accommodate new flights into an existing flight schedule in a short time. We suggest some operational changes such as controlling the aircraft cruise speed, re-timing flight departures and swapping aircraft to open up time for new flights. However, nonlinear fuel cost function, and binary assignment and swapping decisions significantly increase the computational burden of solving scheduling problems. In this thesis, we propose strong mixed integer conic quadratic formulations. Finally, we extend the problem by including a strategic decision to lease an aircraft for introducing new flights. More importantly, we consider the effects of departure time decisions on the probability distribution of random demand. We propose a bounding method based on scenario group-wise decomposition for stochastic programs with decision dependent probabilities.en_US
dc.description.degreePh.D.en_US
dc.description.statementofresponsibilityby Özge Şafak Aydıneren_US
dc.embargo.release2019-12-27
dc.format.extentxi, 184 leaves : illustrations (some color) ; 30 cm.en_US
dc.identifier.itemidB154601
dc.identifier.urihttp://hdl.handle.net/11693/52081
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAircraft cruise speed controlen_US
dc.subjectAirline schedulingen_US
dc.subjectDecision dependent uncertaintyen_US
dc.subjectDecomposition methodsen_US
dc.subjectMixed integer conic quadratic programmingen_US
dc.subjectStochastic programmingen_US
dc.titleOptimizing airline operations under uncertaintyen_US
dc.title.alternativeBelirsizlikler altında havayolu operasyonlarını en iyilemeen_US
dc.typeThesisen_US
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