IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v83y2019icp181-198.html
   My bibliography  Save this article

Stockout risk of production-inventory systems with compound Poisson demands

Author

Listed:
  • (Ai-Chih) Chang, Jasmine
  • Lu, Haibing
  • (Junmin) Shi, Jim

Abstract

Production-inventory systems with continuous production or continuous manufacturing have been implemented in a variety of manufacturing contexts. Most recently, the Commissioner of the FDA has called on drug and biological product manufacturers to begin switching from batch manufacturing processes to continuous production. Motivated by prevailing applications and the emerging and promising landscape in the healthcare and pharmaceutical industries, this paper studies a continuous-review production-inventory system with a constant production rate and compound Poisson demands, in which the cost of the system is assessed via inventory holding, stockout penalty and production costs. For any initial inventory, we derive a closed-form expression for the expected discounted cost function until stockout occurrence. We systemically quantify the stockout risk on four different dimensions (i.e., time, volume, frequency and percentage) and derive explicit expressions for each type of risk metric. The objective is to derive the production rate that minimizes the expected discounted system cost subject to a given risk tolerance level on stockouts. With the aid of the derived explicit forms of stockout risk and the cost function, we develop a computationally-efficient algorithm for the optimal solution. Extensive numerical studies are conducted to illustrate our results with rich insights. Numerically, we show that it is outrageously costly to reduce stockout risk, especially when this risk is relatively low; the value of risk is more sensitive to the stockout risk level if the demand distribution has a higher volatility.

Suggested Citation

  • (Ai-Chih) Chang, Jasmine & Lu, Haibing & (Junmin) Shi, Jim, 2019. "Stockout risk of production-inventory systems with compound Poisson demands," Omega, Elsevier, vol. 83(C), pages 181-198.
  • Handle: RePEc:eee:jomega:v:83:y:2019:i:c:p:181-198
    DOI: 10.1016/j.omega.2018.03.001
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048318302482
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.omega.2018.03.001?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. G. J. Van Houtum & W. H. M. Zijm, 2000. "On the relationship between cost and service models for general inventory systems," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 54(2), pages 127-147, July.
    2. Tang, Christopher S., 2006. "Perspectives in supply chain risk management," International Journal of Production Economics, Elsevier, vol. 103(2), pages 451-488, October.
    3. Yonit Barron & Dror Hermel, 2017. "Shortage decision policies for a fluid production model with MAP arrivals," International Journal of Production Research, Taylor & Francis Journals, vol. 55(14), pages 3946-3969, July.
    4. Benjamin Lev & Howard J. Weiss, 1990. "Inventory Models with Cost Changes," Operations Research, INFORMS, vol. 38(1), pages 53-63, February.
    5. Junmin Shi & Yao Zhao, 2010. "Technical note: Some structural results on acyclic supply chains," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(6), pages 605-613, September.
    6. Yonit Barron, 2016. "Performance analysis of a reflected fluid production/inventory model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 1-31, February.
    7. Michael N. Katehakis & Benjamin Melamed & Jim (Junmin) Shi, 2016. "Cash-Flow Based Dynamic Inventory Management," Production and Operations Management, Production and Operations Management Society, vol. 25(9), pages 1558-1575, September.
    8. Jim (Junmin) Shi & Xiaohang Yue & Yao Zhao, 2014. "Operations sequencing for a multi‐stage production inventory system," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(2), pages 144-154, March.
    9. de Kok, A. G., 1987. "Approximations for operating characteristics in a production-inventory model with variable production rate," European Journal of Operational Research, Elsevier, vol. 29(3), pages 286-297, June.
    10. Junmin Shi & Michael Katehakis & Benjamin Melamed, 2013. "Martingale methods for pricing inventory penalties under continuous replenishment and compound renewal demands," Annals of Operations Research, Springer, vol. 208(1), pages 593-612, September.
    11. B. Lev & D. I. Toof, 1980. "The role of internal storage capacity in fixed cycle production systems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 27(3), pages 477-487, September.
    12. David Perry & Wolfgang Stadje & Shelemyahu Zacks, 2005. "Sporadic and Continuous Clearing Policies for a Production/Inventory System Under an M / G Demand Process," Mathematics of Operations Research, INFORMS, vol. 30(2), pages 354-368, May.
    13. Qi, Lian & Shi, Jim (Junmin) & Xu, Xiaowei, 2015. "Supplier competition and its impact on firm׳s sourcing strategy," Omega, Elsevier, vol. 55(C), pages 91-110.
    14. A. G. de Kok, 1985. "Approximations for a Lost-Sales Production/Inventory Control Model with Service Level Constraints," Management Science, INFORMS, vol. 31(6), pages 729-737, June.
    15. Yonit Barron, 2016. "Performance analysis of a reflected fluid production/inventory model," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 83(1), pages 1-31, February.
    16. Chakraborty, Tulika & Giri, B.C. & Chaudhuri, K.S., 2009. "Production lot sizing with process deterioration and machine breakdown under inspection schedule," Omega, Elsevier, vol. 37(2), pages 257-271, April.
    17. Chang, Hung-Chi & Ho, Chia-Huei, 2010. "Exact closed-form solutions for "optimal inventory model for items with imperfect quality and shortage backordering"," Omega, Elsevier, vol. 38(3-4), pages 233-237, June.
    18. Hans Gerber & Elias Shiu, 1998. "On the Time Value of Ruin," North American Actuarial Journal, Taylor & Francis Journals, vol. 2(1), pages 48-72.
    19. Paul Zipkin, 1986. "Inventory Service-Level Measures: Convexity and Approximation," Management Science, INFORMS, vol. 32(8), pages 975-981, August.
    20. Augustine O. Esogbue & Amar J. Singh, 1976. "A Stochastic Model for an Optimal Priority Bed Distribution Problem in a Hospital Ward," Operations Research, INFORMS, vol. 24(5), pages 884-898, October.
    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. Prak, Dennis & Teunter, Ruud & Babai, Mohamed Zied & Boylan, John E. & Syntetos, Aris, 2021. "Robust compound Poisson parameter estimation for inventory control," Omega, Elsevier, vol. 104(C).
    2. Jian-Jun Wang & Zongli Dai & Wenxuan Zhang & Jim Junmin Shi, 2023. "Operating room scheduling for non-operating room anesthesia with emergency uncertainty," Annals of Operations Research, Springer, vol. 321(1), pages 565-588, February.
    3. Chang, Jasmine (Aichih) & Katehakis, Michael N. & Shi, Jim (Junmin) & Yan, Zhipeng, 2021. "Blockchain-empowered Newsvendor optimization," International Journal of Production Economics, Elsevier, vol. 238(C).
    4. Pablo Azcue & Esther Frostig & Nora Muler, 2023. "Optimal Strategies in a Production Inventory Control Model," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-43, March.
    5. Anushri Maji & Asoke Kumar Bhunia & Shyamal Kumar Mondal, 2022. "A production-reliability-inventory model for a series-parallel system with mixed strategy considering shortage, warranty period, credit period in crisp and stochastic sense," OPSEARCH, Springer;Operational Research Society of India, vol. 59(3), pages 862-907, September.

    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. Jim Shi, 2022. "Optimal continuous production-inventory systems subject to stockout risk," Annals of Operations Research, Springer, vol. 317(2), pages 777-804, October.
    2. Jim (Junmin) Shi & Michael N. Katehakis & Benjamin Melamed & Yusen Xia, 2014. "Production-Inventory Systems with Lost Sales and Compound Poisson Demands," Operations Research, INFORMS, vol. 62(5), pages 1048-1063, October.
    3. Klosterhalfen, Steffen T. & Holzhauer, Falk & Fleischmann, Moritz, 2018. "Control of a continuous production inventory system with production quantity restrictions," European Journal of Operational Research, Elsevier, vol. 268(2), pages 569-581.
    4. Jian-Jun Wang & Zongli Dai & Ai-Chih Chang & Jim Junmin Shi, 2022. "Surgical scheduling by Fuzzy model considering inpatient beds shortage under uncertain surgery durations," Annals of Operations Research, Springer, vol. 315(1), pages 463-505, August.
    5. Zhong-Ping Li & Jian-Jun Wang & Ai-Chih Chang & Jim Shi, 2021. "Capacity reallocation via sinking high-quality resource in a hierarchical healthcare system," Annals of Operations Research, Springer, vol. 300(1), pages 97-135, May.
    6. Wee, Hui Ming & Widyadana, Gede Agus, 2013. "A production model for deteriorating items with stochastic preventive maintenance time and rework process with FIFO rule," Omega, Elsevier, vol. 41(6), pages 941-954.
    7. Ramasesh, Ranga V., 2010. "Lot-sizing decisions under limited-time price incentives: A review," Omega, Elsevier, vol. 38(3-4), pages 118-135, June.
    8. Yonit Barron & David Perry & Wolfgang Stadje, 2016. "A make-to-stock production/inventory model with MAP arrivals and phase-type demands," Annals of Operations Research, Springer, vol. 241(1), pages 373-409, June.
    9. Chang, Jasmine (Aichih) & Katehakis, Michael N. & Shi, Jim (Junmin) & Yan, Zhipeng, 2021. "Blockchain-empowered Newsvendor optimization," International Journal of Production Economics, Elsevier, vol. 238(C).
    10. Chiu, Singa Wang & Chou, Chung-Li & Wu, Wen-Kuei, 2013. "Optimizing replenishment policy in an EPQ-based inventory model with nonconforming items and breakdown," Economic Modelling, Elsevier, vol. 35(C), pages 330-337.
    11. Pablo Azcue & Esther Frostig & Nora Muler, 2023. "Optimal Strategies in a Production Inventory Control Model," Methodology and Computing in Applied Probability, Springer, vol. 25(1), pages 1-43, March.
    12. Huang, He & Xu, Hongyan, 2015. "Dual sourcing and backup production: Coexistence versus exclusivity," Omega, Elsevier, vol. 57(PA), pages 22-33.
    13. Onno Boxma & David Perry & Wolfgang Stadje & Shelley Zacks, 2022. "A compound Poisson EOQ model for perishable items with intermittent high and low demand periods," Annals of Operations Research, Springer, vol. 317(2), pages 439-459, October.
    14. Berthaut, F. & Gharbi, A. & Dhouib, K., 2011. "Joint modified block replacement and production/inventory control policy for a failure-prone manufacturing cell," Omega, Elsevier, vol. 39(6), pages 642-654, December.
    15. Sajadieh, Mohsen S. & Larsen, Christian, 2015. "A coordinated manufacturer-retailer model under stochastic demand and production rate," International Journal of Production Economics, Elsevier, vol. 168(C), pages 64-70.
    16. Baek, Jung Woo & Bae, Yun Han, 2022. "A queuing-inventory model for manufacturing systems with fluid-type inventory," Omega, Elsevier, vol. 111(C).
    17. Jeang, Angus, 2012. "Simultaneous determination of production lot size and process parameters under process deterioration and process breakdown," Omega, Elsevier, vol. 40(6), pages 774-781.
    18. Yonit Barron, 2022. "A probabilistic approach to the stochastic fluid cash management balance problem," Annals of Operations Research, Springer, vol. 312(2), pages 607-645, May.
    19. Azoury, Katy S. & Miyaoka, Julia, 2020. "Optimal and simple approximate solutions to a production-inventory system with stochastic and deterministic demand," European Journal of Operational Research, Elsevier, vol. 286(1), pages 178-189.
    20. Zan Yu & Lianzeng Zhang, 2024. "Computing the Gerber-Shiu function with interest and a constant dividend barrier by physics-informed neural networks," Papers 2401.04378, arXiv.org.

    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:eee:jomega:v:83:y:2019:i:c:p:181-198. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.