IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v44y2022i4d10.1007_s10878-020-00603-2.html
   My bibliography  Save this article

Online economic ordering problem for deteriorating items with limited price information

Author

Listed:
  • Wenqiang Dai

    (University of Electronic Science and Technology of China)

  • Meng Zheng

    (University of Electronic Science and Technology of China)

  • Xu Chen

    (University of Electronic Science and Technology of China)

  • Zhuolin Yang

    (University of Electronic Science and Technology of China)

Abstract

Traditional economic ordering model for deteriorating items assume the procurer have full information about the procurement price. In this paper, we study an online economic ordering problem for constant deteriorating rate items with limited price information under relative performance criterion of the competitive ratio (CR). We provide a simply procurement strategy as well as the optimal ordering quantity for each case. This procurement strategy is real-time and doesn’t require any forecast, i.e., upon the arrival of price, the strategy concerning procurement time and quantity only be made based on arriving price and current inventory level, with entirely arbitrary non-stationary and even adversarial price sequence arrivals. A theoretical closed-form CR is also proven to give the performance guarantee. Our numerical experiments demonstrate even better empirical performance than the corresponding proven worst-case bounds.

Suggested Citation

  • Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 2022. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 44(4), pages 2246-2268, November.
  • Handle: RePEc:spr:jcomop:v:44:y:2022:i:4:d:10.1007_s10878-020-00603-2
    DOI: 10.1007/s10878-020-00603-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-020-00603-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10878-020-00603-2?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Stefano Coniglio & Arie M. C. A. Koster & Nils Spiekermann, 2018. "Lot sizing with storage losses under demand uncertainty," Journal of Combinatorial Optimization, Springer, vol. 36(3), pages 763-788, October.
    2. 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.
    3. Goyal, S. K. & Giri, B. C., 2001. "Recent trends in modeling of deteriorating inventory," European Journal of Operational Research, Elsevier, vol. 134(1), pages 1-16, October.
    4. Wilco Van den Heuvel & Albert P. M. Wagelmans, 2010. "Worst-Case Analysis for a General Class of Online Lot-Sizing Heuristics," Operations Research, INFORMS, vol. 58(1), pages 59-67, February.
    5. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
    6. Liu, Ming & Chu, Chengbin & Xu, Yinfeng & Zheng, Feifeng, 2010. "An optimal online algorithm for single machine scheduling with bounded delivery times," European Journal of Operational Research, Elsevier, vol. 201(3), pages 693-700, March.
    7. Wenqiang Dai & Xianju Zeng, 2010. "Incremental Facility Location Problem and Its Competitive Algorithms," Journal of Combinatorial Optimization, Springer, vol. 20(3), pages 307-320, October.
    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. David G. Luenberger & Yinyu Ye, 2016. "Linear and Nonlinear Programming," International Series in Operations Research and Management Science, Springer, edition 4, number 978-3-319-18842-3, September.
    10. Zheng, Feifeng & Cheng, Yongxi & Xu, Yinfeng & Liu, Ming, 2013. "Competitive strategies for an online generalized assignment problem with a service consecution constraint," European Journal of Operational Research, Elsevier, vol. 229(1), pages 59-66.
    11. Guanqun Ni, 2020. "Replenishment policy for a purchase-to-order seller: a tradeoff between ordering cost and delay cost," International Journal of Production Research, Taylor & Francis Journals, vol. 58(4), pages 1239-1254, February.
    12. Wenqiang Dai & Zhuolin Yang & Yi Feng & Meng Zheng, 2020. "Real-time procurement policy with yield and price uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 58(3), pages 758-782, February.
    13. Mohr, Esther, 2017. "Optimal replenishment under price uncertainty," European Journal of Operational Research, Elsevier, vol. 258(1), pages 136-143.
    14. Larsen, Kim S. & Wøhlk, Sanne, 2010. "Competitive analysis of the online inventory problem," European Journal of Operational Research, Elsevier, vol. 207(2), pages 685-696, December.
    15. 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)

    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. Wenqiang Dai & Meng Zheng & Xu Chen & Zhuolin Yang, 0. "Online economic ordering problem for deteriorating items with limited price information," Journal of Combinatorial Optimization, Springer, vol. 0, pages 1-23.
    2. Guanqun Ni, 2023. "An improved online replenishment policy and its competitive ratio analysis for a purchase-to-order seller," Journal of Combinatorial Optimization, Springer, vol. 46(2), pages 1-14, September.
    3. Janssen, Larissa & Diabat, Ali & Sauer, Jürgen & Herrmann, Frank, 2018. "A stochastic micro-periodic age-based inventory replenishment policy for perishable goods," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 445-465.
    4. Madhukar Nagare & Pankaj Dutta & Pravin Suryawanshi, 2020. "Optimal procurement and discount pricing for single-period non-instantaneous deteriorating products with promotional efforts," Operational Research, Springer, vol. 20(1), pages 89-117, March.
    5. Massonnet, G. & Gayon, J.-P. & Rapine, C., 2014. "Approximation algorithms for deterministic continuous-review inventory lot-sizing problems with time-varying demand," European Journal of Operational Research, Elsevier, vol. 234(3), pages 641-649.
    6. Ehsan Ahmadi & Dale T. Masel & Seth Hostetler & Reza Maihami & Iman Ghalehkhondabi, 2020. "A centralized stochastic inventory control model for perishable products considering age-dependent purchase price and lead time," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(1), pages 231-269, April.
    7. Kun-Jen Chung & Jui-Jung Liao & Hari Mohan Srivastava & Shih-Fang Lee & Shy-Der Lin, 2021. "The EOQ Model for Deteriorating Items with a Conditional Trade Credit Linked to Order Quantity in a Supply Chain System," Mathematics, MDPI, vol. 9(18), pages 1-28, September.
    8. Jake Clarkson & Michael A. Voelkel & Anna‐Lena Sachs & Ulrich W. Thonemann, 2023. "The periodic review model with independent age‐dependent lifetimes," Production and Operations Management, Production and Operations Management Society, vol. 32(3), pages 813-828, March.
    9. Dai, Wenqiang & Dong, Yucheng & Zhang, Xiaotian, 2016. "Competitive analysis of the online financial lease problem," European Journal of Operational Research, Elsevier, vol. 250(3), pages 865-873.
    10. Chaitanyakumar N. Rapolu & Deepa H. Kandpal, 2020. "Joint pricing, advertisement, preservation technology investment and inventory policies for non-instantaneous deteriorating items under trade credit," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 274-300, June.
    11. Li, Guiping & He, Xiuli & Zhou, Jing & Wu, Hao, 2019. "Pricing, replenishment and preservation technology investment decisions for non-instantaneous deteriorating items," Omega, Elsevier, vol. 84(C), pages 114-126.
    12. Yan Shi & Zhiyong Zhang & Sunil Tiwari & Zhiwen Tao, 2022. "Retailer's optimal strategy for a perishable product with increasing demand under various payment schemes," Annals of Operations Research, Springer, vol. 315(2), pages 899-929, August.
    13. Sadia Samar Ali & Haripriya Barman & Rajbir Kaur & Hana Tomaskova & Sankar Kumar Roy, 2021. "Multi-Product Multi Echelon Measurements of Perishable Supply Chain: Fuzzy Non-Linear Programming Approach," Mathematics, MDPI, vol. 9(17), pages 1-27, August.
    14. Beullens, Patrick & Ghiami, Yousef, 2022. "Waste reduction in the supply chain of a deteriorating food item – Impact of supply structure on retailer performance," European Journal of Operational Research, Elsevier, vol. 300(3), pages 1017-1034.
    15. N. Saranya & A. Shophia Lawrence, 2019. "A stochastic inventory system with replacement of perishable items," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 563-582, June.
    16. Adam N. Elmachtoub & Retsef Levi, 2015. "From Cost Sharing Mechanisms to Online Selection Problems," Mathematics of Operations Research, INFORMS, vol. 40(3), pages 542-557, March.
    17. Mohr, Esther, 2017. "Optimal replenishment under price uncertainty," European Journal of Operational Research, Elsevier, vol. 258(1), pages 136-143.
    18. Lopez Alvarez, Jose A. & Buijs, Paul & Kilic, Onur A. & Vis, Iris F.A., 2020. "An inventory control policy for liquefied natural gas as a transportation fuel," Omega, Elsevier, vol. 90(C).
    19. Gorria, Carlos & Lezaun, Mikel & López, F. Javier, 2022. "Performance measures of nonstationary inventory models for perishable products under the EWA policy," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1137-1150.
    20. Tiwari, Sunil & Jaggi, Chandra K. & Gupta, Mamta & Cárdenas-Barrón, Leopoldo Eduardo, 2018. "Optimal pricing and lot-sizing policy for supply chain system with deteriorating items under limited storage capacity," International Journal of Production Economics, Elsevier, vol. 200(C), pages 278-290.

    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:jcomop:v:44:y:2022:i:4:d:10.1007_s10878-020-00603-2. 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.