An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control
dc.citation.epage | 57 | en_US |
dc.citation.spage | 38 | en_US |
dc.citation.volumeNumber | 68 | en_US |
dc.contributor.author | Gürkan, H. | en_US |
dc.contributor.author | Gürel, S. | en_US |
dc.contributor.author | Aktürk, M. S. | en_US |
dc.date.accessioned | 2018-04-12T10:52:28Z | |
dc.date.available | 2018-04-12T10:52:28Z | |
dc.date.issued | 2016 | en_US |
dc.department | Department of Industrial Engineering | en_US |
dc.description.abstract | To place an emphasis on profound relations among airline schedule planning problems and to mitigate the effect of unexpected delays, we integrate schedule design, fleet assignment and aircraft routing problems within a daily planning horizon while passengers' connection service levels are ensured via chance constraints. We propose a nonlinear mixed integer programming model due to the nonlinear fuel consumption and CO2 emission cost terms in the objective function, which is handled by second order conic reformulation. The key contribution of this study is to take into account the cruise time control for the first time in an integrated model of these three stages of airline operations. Changing cruise times of flights in an integrated model enables to construct a schedule to increase utilization of fuel efficient aircraft and even to decrease total number of aircraft needed while satisfying the same service level and maintenance requirements for aircraft fleeting and routing. There is a critical tradeoff between the number of aircraft needed to fulfill the required flights and overall operational expenses. We also propose two heuristic methods to solve larger size problems. Finally, computational results using real data obtained from a major U.S. carrier are presented to demonstrate potential profitability in applying the proposed solution methods. | en_US |
dc.description.provenance | Made available in DSpace on 2018-04-12T10:52:28Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2016 | en |
dc.identifier.doi | 10.1016/j.trc.2016.03.002 | en_US |
dc.identifier.eissn | 1879-2359 | |
dc.identifier.issn | 0968-090X | |
dc.identifier.uri | http://hdl.handle.net/11693/36762 | |
dc.language.iso | English | en_US |
dc.publisher | Elsevier | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1016/j.trc.2016.03.002 | en_US |
dc.source.title | Transportation Research Part C | en_US |
dc.subject | Aircraft fleeting and routing | en_US |
dc.subject | Airline scheduling | en_US |
dc.subject | Cruise time controllability | en_US |
dc.subject | Second order cone programming | en_US |
dc.subject | Aircraft | en_US |
dc.subject | Carbon dioxide | en_US |
dc.subject | Heuristic methods | en_US |
dc.subject | Integer programming | en_US |
dc.subject | Problem solving | en_US |
dc.subject | Scheduling | en_US |
dc.subject | Airline scheduling | en_US |
dc.subject | Computational results | en_US |
dc.subject | Cruise time | en_US |
dc.subject | Larger size problems | en_US |
dc.subject | Maintenance requirement | en_US |
dc.subject | Non-linear mixed integer programming | en_US |
dc.subject | Objective functions | en_US |
dc.subject | Second-order cone programming | en_US |
dc.subject | Air transportation | en_US |
dc.title | An integrated approach for airline scheduling, aircraft fleeting and routing with cruise speed control | en_US |
dc.type | Article | en_US |
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