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Airline network revenue management by multistage stochastic programming

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  • Andris Möller
  • Werner Römisch
  • Klaus Weber

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  • Andris Möller & Werner Römisch & Klaus Weber, 2008. "Airline network revenue management by multistage stochastic programming," Computational Management Science, Springer, vol. 5(4), pages 355-377, October.
    • Handle: RePEc:spr:comgts:v:5:y:2008:i:4:p:355-377
    DOI: 10.1007/s10287-007-0058-8
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    References listed on IDEAS

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    1. Kalyan Talluri & Garrett van Ryzin, 1999. "A Randomized Linear Programming Method for Computing Network Bid Prices," Transportation Science, INFORMS, vol. 33(2), pages 207-216, May.
    2. Kalyan Talluri & Garrett van Ryzin, 1998. "An Analysis of Bid-Price Controls for Network Revenue Management," Management Science, INFORMS, vol. 44(11-Part-1), pages 1577-1593, November.
    3. Jeffrey I. McGill & Garrett J. van Ryzin, 1999. "Revenue Management: Research Overview and Prospects," Transportation Science, INFORMS, vol. 33(2), pages 233-256, May.
    4. de Boer, Sanne V. & Freling, Richard & Piersma, Nanda, 2002. "Mathematical programming for network revenue management revisited," European Journal of Operational Research, Elsevier, vol. 137(1), pages 72-92, February.
    5. William L. Cooper & Tito Homem-de-Mello & Anton J. Kleywegt, 2006. "Models of the Spiral-Down Effect in Revenue Management," Operations Research, INFORMS, vol. 54(5), pages 968-987, October.
    6. Jitka Dupačová & Giorgio Consigli & Stein Wallace, 2000. "Scenarios for Multistage Stochastic Programs," Annals of Operations Research, Springer, vol. 100(1), pages 25-53, December.
    7. Klein, Robert & Petrick, Anita, 2003. "Revenue Management : eine weitere Erfolgsstory des Operations Research," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 20672, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    8. Dimitris Bertsimas & Sanne de Boer, 2005. "Simulation-Based Booking Limits for Airline Revenue Management," Operations Research, INFORMS, vol. 53(1), pages 90-106, February.
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    Cited by:

    1. McAleer, M.J. & Jiménez-Martín, J.A. & Pérez-Amaral, T., 2008. "A decision rule to minimize daily capital charges in forecasting value-at-risk," Econometric Institute Research Papers EI 2008-34, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Zhiping Chen & Wentao Ma, 2024. "A Bayesian approach to data-driven multi-stage stochastic optimization," Journal of Global Optimization, Springer, vol. 90(2), pages 401-428, October.
    3. L. F. Escudero & J. F. Monge & D. Romero Morales & J. Wang, 2013. "Expected Future Value Decomposition Based Bid Price Generation for Large-Scale Network Revenue Management," Transportation Science, INFORMS, vol. 47(2), pages 181-197, May.
    4. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    5. Ma, Qiuzhuo & Song, Haiqing & Zhu, Wenbin, 2018. "Low-carbon airline fleet assignment: A compromise approach," Journal of Air Transport Management, Elsevier, vol. 68(C), pages 86-102.
    6. Gatzert, Nadine & Martin, Alexander & Schmidt, Martin & Seith, Benjamin & Vogl, Nikolai, 2021. "Portfolio optimization with irreversible long-term investments in renewable energy under policy risk: A mixed-integer multistage stochastic model and a moving-horizon approach," European Journal of Operational Research, Elsevier, vol. 290(2), pages 734-748.

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