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Revenue management policies for the truck rental industry

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  • Guerriero, Francesca
  • Miglionico, Giovanna
  • Olivito, Filomena

Abstract

In this paper, we consider the problem of managing a fleet of trucks with different capacity to serve the requests of different customers that arise randomly over time. The problem is formulated via dynamic programming. Linear programming approximations of the problem are presented and their solutions are exploited to develop partitioned booking limits and bid prices policies. The numerical experiments show that the proposed policies can be profitably used in supporting the decision maker.

Suggested Citation

  • Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2012. "Revenue management policies for the truck rental industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 202-214.
    • Handle: RePEc:eee:transe:v:48:y:2012:i:1:p:202-214
    DOI: 10.1016/j.tre.2011.07.006
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    References listed on IDEAS

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    1. William L. Cooper, 2002. "Asymptotic Behavior of an Allocation Policy for Revenue Management," Operations Research, INFORMS, vol. 50(4), pages 720-727, August.
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    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. Wen-Chyuan Chiang & Jason C.H. Chen & Xiaojing Xu, 2007. "An overview of research on revenue management: current issues and future research," International Journal of Revenue Management, Inderscience Enterprises Ltd, vol. 1(1), pages 97-128.
    6. Huseyin Topaloglu & Warren B. Powell, 2006. "Dynamic-Programming Approximations for Stochastic Time-Staged Integer Multicommodity-Flow Problems," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 31-42, February.
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    Cited by:

    1. Oliveira, Beatriz Brito & Carravilla, Maria Antónia & Oliveira, José Fernando, 2017. "Fleet and revenue management in car rental companies: A literature review and an integrated conceptual framework," Omega, Elsevier, vol. 71(C), pages 11-26.
    2. Guerriero, Francesca & Miglionico, Giovanna & Olivito, Filomena, 2014. "Strategic and operational decisions in restaurant revenue management," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1119-1132.
    3. Wang, Shuaian & Wang, Hua & Meng, Qiang, 2015. "Itinerary provision and pricing in container liner shipping revenue management," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 135-146.
    4. Christine Fricker & Nicolas Gast, 2016. "Incentives and redistribution in homogeneous bike-sharing systems with stations of finite capacity," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 5(3), pages 261-291, August.
    5. Wang, Tingsong & Xing, Zheng & Hu, Hongtao & Qu, Xiaobo, 2019. "Overbooking and delivery-delay-allowed strategies for container slot allocation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 433-447.

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