Abstract The aviation industry has recently experienced a fast move toward the hybridization of airline business models. This has remarkably affected airline network structures, moving from a neat contraposition between hub-and-spoke networks (typical of full-service carriers) and point-to-point networks (typical of low-cost carriers) to more hybrid architectures. While literature has widely documented the ongoing restructuring of airline networks, the development of decision support systems in this respect has been rather scant. In this paper, we develop an optimization-based approach—referred to Integrated Connection Planning and Passenger Allocation Model (ICPPAM)—to support low-cost airlines in the early stage of connection planning, encompassing the definition of the most promising transfer airports and the set of optimal connecting itineraries to be rolled out over an existing network of flights. The ICPPAM solves the passenger mix problem on every flight segment, leveraging endogenous demand estimates based on an empirical discrete choice model. We demonstrate the applicability of the proposed approach to the large-scale network of Ryanair in 2019. Results highlight that the proposed approach can significantly aid airlines’ decision-making, leading to significant revenue improvements (up to 4.4%) and shedding insights into network development alternatives.

    Highlights Optimization-based decision support for designing hybrid airline networks (ICPPAM) ICPPAM identifies promising transfer airports and optimal connecting services ICPPAM considers endogenous demand estimates based on an empirical discrete choice model Real-world case study considering the large-scale network of Ryanair in 2019 Application of ICCPAM highlights seizable revenue increase and network development insights


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    Titel :

    An integrated connection planning and passenger allocation model for low-cost carriers


    Beteiligte:


    Erscheinungsdatum :

    2021-10-25




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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