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Increasing the Revenue of Self-Storage Warehouses by Optimizing Order Scheduling

Author

Listed:
  • Xiandong Zhang

    (Fudan University [Shanghai])

  • Yeming Gong

    (EM - EMLyon Business School)

  • Shuyu Zhou

    (Erasmus University Rotterdam)

  • René de Koster

    (Erasmus University Rotterdam)

  • Steef van de Velde

    (Erasmus University Rotterdam)

Abstract

We consider a self-storage warehouse, facing storage orders for homogeneous or heterogeneous storage units over a certain time horizon. The warehouse operations manager needs to decide which storage orders to accept and schedule them across different storage units to maximize revenue. We model warehouse operations as scheduling n independent multiprocessor tasks with given start and end times, with an objective to maximize revenue. With operational constraints like the maximal upscaling level, precedence order constraints, and maximal idle time, the established mixed-integer program cannot be efficiently solved by commercial softwares. We therefore propose a column generation approach and a branch-and-price method to find an optimal schedule. Computational experiments show that, compared with current methods in self-storage warehouses, our method can significantly increase the revenue.

Suggested Citation

  • Xiandong Zhang & Yeming Gong & Shuyu Zhou & René de Koster & Steef van de Velde, 2016. "Increasing the Revenue of Self-Storage Warehouses by Optimizing Order Scheduling," Post-Print hal-02313355, HAL.
    • Handle: RePEc:hal:journl:hal-02313355
    DOI: 10.1016/j.ejor.2015.12.044
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    Citations

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    Cited by:

    1. Shi, Ye & Yu, Yugang & Dong, Yuxuan, 2021. "Warehousing platform’s revenue management: A dynamic model of coordinating space allocation for self-use and rent," European Journal of Operational Research, Elsevier, vol. 293(1), pages 167-176.
    2. Shuyu Zhou & Yeming (Yale) Gong & René de Koster, 2016. "Designing self-storage warehouses with customer choice," International Journal of Production Research, Taylor & Francis Journals, vol. 54(10), pages 3080-3104, May.
    3. Zhe Yuan & Haoxuan Xu & Yeming (Yale) Gong & Chengbin Chu & Jinlong Zhang, 2017. "Designing public storage warehouses with high demand for revenue maximisation," International Journal of Production Research, Taylor & Francis Journals, vol. 55(13), pages 3686-3700, July.
    4. Boysen, Nils & Briskorn, Dirk & Schwerdfeger, Stefan, 2019. "Matching supply and demand in a sharing economy: Classification, computational complexity, and application," European Journal of Operational Research, Elsevier, vol. 278(2), pages 578-595.
    5. Joonyup Eun & Chang Sup Sung & Eun-Seok Kim, 2017. "Maximizing total job value on a single machine with job selection," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(9), pages 998-1005, September.

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