IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v223y2014i1p433-44910.1007-s10479-014-1620-8.html
   My bibliography  Save this article

Probability-free solutions to the non-stationary newsvendor problem

Author

Listed:
  • Yong Zhang
  • Vladimir Vovk
  • Weiguo Zhang

Abstract

This paper concerns the multi-period newsvendor problem. In this problem, the decision maker has to decide the order quantity of an item in the subsequent period in which the demand is usually unknown. No statistical assumptions are made about the unknown demand. We adopt an online learning method from the field of prediction with expert advice to study the non-stationary newsvendor problem. We propose newsvendor strategies for both real-valued and integer order quantities. Taking the non-stationary strategies that can switch between different order quantities as benchmark, we prove that our proposed strategies can guarantee that the newsvendor’s cumulative gains are almost as large as those of the best switching strategies with not too many switches. Simple computational experiments are further performed to illustrate the effectiveness of our strategies. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Yong Zhang & Vladimir Vovk & Weiguo Zhang, 2014. "Probability-free solutions to the non-stationary newsvendor problem," Annals of Operations Research, Springer, vol. 223(1), pages 433-449, December.
    • Handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:433-449:10.1007/s10479-014-1620-8
    DOI: 10.1007/s10479-014-1620-8
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-014-1620-8
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10479-014-1620-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Herbert E. Scarf, 1960. "Some remarks on bayes solutions to the inventory problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 7(4), pages 591-596, December.
    2. Moon, Ilkyeong & Choi, Sangjin, 1997. "Distribution free procedures for make-to-order (MTO), make-in-advance (MIA), and composite policies," International Journal of Production Economics, Elsevier, vol. 48(1), pages 21-28, January.
    3. Donald L. Iglehart, 1964. "The Dynamic Inventory Problem with Unknown Demand Distribution," Management Science, INFORMS, vol. 10(3), pages 429-440, April.
    4. Katy S. Azoury, 1985. "Bayes Solution to Dynamic Inventory Models Under Unknown Demand Distribution," Management Science, INFORMS, vol. 31(9), pages 1150-1160, September.
    5. Liao, Yi & Banerjee, Avijit & Yan, Changyuan, 2011. "A distribution-free newsvendor model with balking and lost sales penalty," International Journal of Production Economics, Elsevier, vol. 133(1), pages 224-227, September.
    6. Alfares, Hesham K. & Elmorra, Hassan H., 2005. "The distribution-free newsboy problem: Extensions to the shortage penalty case," International Journal of Production Economics, Elsevier, vol. 93(1), pages 465-477, January.
    7. Woonghee Tim Huh & Ganesh Janakiraman & John A. Muckstadt & Paat Rusmevichientong, 2009. "An Adaptive Algorithm for Finding the Optimal Base-Stock Policy in Lost Sales Inventory Systems with Censored Demand," Mathematics of Operations Research, INFORMS, vol. 34(2), pages 397-416, May.
    8. Michael R. Wagner, 2010. "Fully Distribution-Free Profit Maximization: The Inventory Management Case," Mathematics of Operations Research, INFORMS, vol. 35(4), pages 728-741, November.
    9. I Moon & E A Silver, 2000. "The multi-item newsvendor problem with a budget constraint and fixed ordering costs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(5), pages 602-608, May.
    10. Woonghee Tim Huh & Paat Rusmevichientong, 2009. "A Nonparametric Asymptotic Analysis of Inventory Planning with Censored Demand," Mathematics of Operations Research, INFORMS, vol. 34(1), pages 103-123, February.
    11. Michael O. Ball & Maurice Queyranne, 2009. "Toward Robust Revenue Management: Competitive Analysis of Online Booking," Operations Research, INFORMS, vol. 57(4), pages 950-963, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Janssen, Larissa & Claus, Thorsten & Sauer, Jürgen, 2016. "Literature review of deteriorating inventory models by key topics from 2012 to 2015," International Journal of Production Economics, Elsevier, vol. 182(C), pages 86-112.
    2. Senlin Zhao & Qinghua Zhu, 2017. "Remanufacturing supply chain coordination under the stochastic remanufacturability rate and the random demand," Annals of Operations Research, Springer, vol. 257(1), pages 661-695, October.
    3. Yong Zhang & Xingyu Yang & Weiguo Zhang & Weiwei Chen, 2020. "Online ordering rules for the multi-period newsvendor problem with quantity discounts," Annals of Operations Research, Springer, vol. 288(1), pages 495-524, May.
    4. Rui Wang & Xiao Yan & Chuanjin Zhu, 2023. "Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution," SAGE Open, , vol. 13(2), pages 21582440231, June.
    5. Zhang, Guoqing & Shi, Jianmai & Chaudhry, Sohail S. & Li, Xindan, 2019. "Multi-period multi-product acquisition planning with uncertain demands and supplier quantity discounts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 132(C), pages 117-140.
    6. Tal Avinadav, 2015. "Continuous accounting of inventory costs with Brownian-motion and Poisson demand processes," Annals of Operations Research, Springer, vol. 229(1), pages 85-102, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Charles X. & Webster, Scott & Zhang, Sidong, 2014. "Robust price-setting newsvendor model with interval market size and consumer willingness-to-pay," International Journal of Production Economics, Elsevier, vol. 154(C), pages 100-112.
    2. Hao Yuan & Qi Luo & Cong Shi, 2021. "Marrying Stochastic Gradient Descent with Bandits: Learning Algorithms for Inventory Systems with Fixed Costs," Management Science, INFORMS, vol. 67(10), pages 6089-6115, October.
    3. Aditya Jain & Nils Rudi & Tong Wang, 2015. "Demand Estimation and Ordering Under Censoring: Stock-Out Timing Is (Almost) All You Need," Operations Research, INFORMS, vol. 63(1), pages 134-150, February.
    4. Mila Nambiar & David Simchi‐Levi & He Wang, 2021. "Dynamic Inventory Allocation with Demand Learning for Seasonal Goods," Production and Operations Management, Production and Operations Management Society, vol. 30(3), pages 750-765, March.
    5. Rui Wang & Xiao Yan & Chuanjin Zhu, 2023. "Solving a Distribution-Free Multi-Period Newsvendor Problem With Advance Purchase Discount via an Online Ordering Solution," SAGE Open, , vol. 13(2), pages 21582440231, June.
    6. Mostard, Julien & de Koster, Rene & Teunter, Ruud, 2005. "The distribution-free newsboy problem with resalable returns," International Journal of Production Economics, Elsevier, vol. 97(3), pages 329-342, September.
    7. Li, Tianyun & Fang, Weiguo & Baykal-Gürsoy, Melike, 2021. "Two-stage inventory management with financing under demand updates," International Journal of Production Economics, Elsevier, vol. 232(C).
    8. Arnab Bisi & Maqbool Dada, 2007. "Dynamic learning, pricing, and ordering by a censored newsvendor," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(4), pages 448-461, June.
    9. Kaijie Zhu & Ulrich W. Thonemann, 2004. "An adaptive forecasting algorithm and inventory policy for products with short life cycles," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(5), pages 633-653, August.
    10. Woonghee Tim Huh & Retsef Levi & Paat Rusmevichientong & James B. Orlin, 2011. "Adaptive Data-Driven Inventory Control with Censored Demand Based on Kaplan-Meier Estimator," Operations Research, INFORMS, vol. 59(4), pages 929-941, August.
    11. Lin An & Andrew A. Li & Benjamin Moseley & R. Ravi, 2023. "The Nonstationary Newsvendor with (and without) Predictions," Papers 2305.07993, arXiv.org, revised Feb 2025.
    12. Rong Li & Jing‐Sheng Jeannette Song & Shuxiao Sun & Xiaona Zheng, 2022. "Fight inventory shrinkage: Simultaneous learning of inventory level and shrinkage rate," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2477-2491, June.
    13. Li, Zhaolin & Fu, Qi (Grace), 2017. "Robust inventory management with stock-out substitution," International Journal of Production Economics, Elsevier, vol. 193(C), pages 813-826.
    14. Meng Qi & Ho‐Yin Mak & Zuo‐Jun Max Shen, 2020. "Data‐driven research in retail operations—A review," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(8), pages 595-616, December.
    15. Satya S. Malladi & Alan L. Erera & Chelsea C. White, 2023. "Inventory control with modulated demand and a partially observed modulation process," Annals of Operations Research, Springer, vol. 321(1), pages 343-369, February.
    16. Harun Avci & Kagan Gokbayrak & Emre Nadar, 2020. "Structural Results for Average‐Cost Inventory Models with Markov‐Modulated Demand and Partial Information," Production and Operations Management, Production and Operations Management Society, vol. 29(1), pages 156-173, January.
    17. Michael R. Wagner, 2010. "Fully Distribution-Free Profit Maximization: The Inventory Management Case," Mathematics of Operations Research, INFORMS, vol. 35(4), pages 728-741, November.
    18. Gokhan Metan & Aurélie Thiele, 2016. "Protecting the data-driven newsvendor against rare events: a correction-term approach," Computational Management Science, Springer, vol. 13(3), pages 459-482, July.
    19. Cong Shi & Weidong Chen & Izak Duenyas, 2016. "Technical Note—Nonparametric Data-Driven Algorithms for Multiproduct Inventory Systems with Censored Demand," Operations Research, INFORMS, vol. 64(2), pages 362-370, April.
    20. Yossi Aviv, 2003. "A Time-Series Framework for Supply-Chain Inventory Management," Operations Research, INFORMS, vol. 51(2), pages 210-227, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:223:y:2014:i:1:p:433-449:10.1007/s10479-014-1620-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.