Integrating Flight Scheduling, Fleet Assignment, and Aircraft Routing Problems with Codesharing Agreements under Stochastic Environment

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dc.authoridKiziloglu, Kubra/0000-0003-1390-6357
dc.contributor.authorKiziloglu, Kuebra
dc.contributor.authorSakalli, uemit Sami
dc.contributor.authorEllerbroek, Joost
dc.date.accessioned2025-01-21T16:41:49Z
dc.date.available2025-01-21T16:41:49Z
dc.date.issued2023
dc.departmentKırıkkale Üniversitesi
dc.description.abstractAirlines face the imperative of resource management to curtail costs, necessitating the solution of several optimization problems such as flight planning, fleet assignment, aircraft routing, and crew scheduling. These problems present some challenges. The first pertains to the common practice of addressing these problems independently, potentially leading to locally optimal outcomes due to their interconnected nature. The second challenge lies in the inherent uncertainty associated with parameters like demand and non-cruise time. On the other hand, airlines can employ a strategy known as codesharing, wherein they operate shared flights, in order to minimize these challenges. In this study, we introduce a novel mathematical model designed to optimize flight planning, fleet assignment, and aircraft routing decisions concurrently, while accommodating for codesharing. This model is formulated as a three-stage non-linear mixed-integer problem, with stochastic parameters representing the demand and non-cruise time. For smaller-scale problems, optimization software can effectively solve the model. However, as the number of flights increases, conventional software becomes inadequate. Moreover, considering a wide array of scenarios for stochastic parameters leads to more robust results; however, it is not enabled because of the limitations of optimization software. In this work, we introduce two new simulation-based metaheuristic algorithms for solving large-dimensional problems, collectively called simheuristic. These algorithms integrate the Monte Carlo simulation technique into Simulated Annealing and Cuckoo Search. We have applied these simheuristic algorithms to various problem samples of different flight sizes and scenarios. The results demonstrate the efficacy of our proposed modeling and solution approaches in efficiently addressing flight scheduling, fleet assignment, and aircraft routing problems within acceptable timeframes.
dc.identifier.doi10.3390/aerospace10121031
dc.identifier.issn2226-4310
dc.identifier.issue12
dc.identifier.scopus2-s2.0-85180180209
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3390/aerospace10121031
dc.identifier.urihttps://hdl.handle.net/20.500.12587/24961
dc.identifier.volume10
dc.identifier.wosWOS:001137824700001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofAerospace
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241229
dc.subjectflight scheduling; fleet assignment; aircraft routing; simheuristic; simulated annealing; cuckoo search
dc.titleIntegrating Flight Scheduling, Fleet Assignment, and Aircraft Routing Problems with Codesharing Agreements under Stochastic Environment
dc.typeArticle

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