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Demand-Oriented Integrated Scheduling for Point-to-Point Airlines

Author

Listed:
  • Oliver Faust

    (University of Augsburg, 86159 Augsburg, Germany)

  • Jochen Gönsch

    (Mercator School of Management, University of Duisburg–Essen, 47057 Duisburg, Germany)

  • Robert Klein

    (University of Augsburg, 86159 Augsburg, Germany)

Abstract

Optimizing an airline schedule usually comprises multiple planning stages. These are the choice of flights to offer (schedule design), the assignment of fleets to flight legs (fleet assignment), and the construction of rotations under consideration of maintenance constraints (aircraft maintenance routing). Moreover, the airline must assign crews to all flights (crew scheduling). Traditionally, either these scheduling stages are considered sequentially or an existing schedule is modified to cope with the arising complexity issue. More recently, some authors have developed models that integrate adjacent stages. In this paper, outcomes of a research project with airline information technology provider Lufthansa Systems are presented. We consider the case of a small to medium-sized point-to-point airline with a homogeneous fleet. Hence, fleet assignment is omitted, which offers the possibility to solve schedule design and aircraft maintenance routing simultaneously. Our approach explicitly accounts for passengers’ return flight demand and for marginal revenues declining with increasing seat capacity, hence, anticipating the effects of capacity control in revenue management systems. To solve the arising integrated mixed-integer problem, a branch-and-price approach and a column generation-based heuristic have been developed. An extensive numerical study, using data from a major European airline provided by Lufthansa Systems, shows that the presented approaches yield high-quality solutions to real-world problem instances within a reasonable time.

Suggested Citation

  • Oliver Faust & Jochen Gönsch & Robert Klein, 2017. "Demand-Oriented Integrated Scheduling for Point-to-Point Airlines," Transportation Science, INFORMS, vol. 51(1), pages 196-213, February.
  • Handle: RePEc:inm:ortrsc:v:51:y:2017:i:1:p:196-213
    DOI: 10.1287/trsc.2016.0693
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    2. He, Yonghuan & Ma, Hoi-Lam & Park, Woo-Yong & Liu, Shi Qiang & Chung, Sai-Ho, 2023. "Maximizing robustness of aircraft routing with heterogeneous maintenance tasks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 177(C).
    3. Jing Zhou, 2023. "Airline capacity distribution under financial budget and resource consideration," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-29, July.
    4. Kenan, Nabil & Jebali, Aida & Diabat, Ali, 2018. "The integrated aircraft routing problem with optional flights and delay considerations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 355-375.
    5. Xu, Yifan & Wandelt, Sebastian & Sun, Xiaoqian, 2021. "Airline integrated robust scheduling with a variable neighborhood search based heuristic," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 181-203.
    6. Renan P. de Oliveira & Alessandro V. M. Oliveira & Gui Lohmann, 2021. "A Network-Design Analysis of Airline Business Model Adaptation in the Face of Competition and Consolidation," Transportation Science, INFORMS, vol. 55(2), pages 532-548, March.
    7. Birolini, Sebastian & Besana, Emanuele & Cattaneo, Mattia & Redondi, Renato & Sallan, Jose Maria, 2022. "An integrated connection planning and passenger allocation model for low-cost carriers," Journal of Air Transport Management, Elsevier, vol. 99(C).
    8. Cacchiani, Valentina & Salazar-González, Juan-José, 2020. "Heuristic approaches for flight retiming in an integrated airline scheduling problem of a regional carrier," Omega, Elsevier, vol. 91(C).

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