IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v238y2014i1p122-129.html
   My bibliography  Save this article

Production planning and pricing policy in a make-to-stock system with uncertain demand subject to machine breakdowns

Author

Listed:
  • Shi, Xiutian
  • Shen, Houcai
  • Wu, Ting
  • Cheng, T.C.E.

Abstract

We consider a make-to-stock system served by an unreliable machine that produces one type of product, which is sold to customers at one of two possible prices depending on the inventory level at the time when a customer arrives (i.e., the decision point). The system manager must determine the production level and selling price at each decision point. We first show that the optimal production and pricing policy is a threshold control, which is characterized by three threshold parameters under both the long-run discounted profit and long-run average profit criteria. We then establish the structural relationships among the three threshold parameters that production is off when inventory is above the threshold, and that the optimal selling price should be low when inventory is above the threshold under the scenario where the machine is down or up. Finally we provide some numerical examples to illustrate the analytical results and gain additional insights.

Suggested Citation

  • Shi, Xiutian & Shen, Houcai & Wu, Ting & Cheng, T.C.E., 2014. "Production planning and pricing policy in a make-to-stock system with uncertain demand subject to machine breakdowns," European Journal of Operational Research, Elsevier, vol. 238(1), pages 122-129.
  • Handle: RePEc:eee:ejores:v:238:y:2014:i:1:p:122-129
    DOI: 10.1016/j.ejor.2014.03.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221714002318
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Mohebbi, Esmail, 2006. "A production-inventory model with randomly changing environmental conditions," European Journal of Operational Research, Elsevier, vol. 174(1), pages 539-552, October.
    2. Sanajian, Nima & BalcIog[small tilde]lu, BarIs, 2009. "The impact of production time variability on make-to-stock queue performance," European Journal of Operational Research, Elsevier, vol. 194(3), pages 847-855, May.
    3. Mayorga, Maria E. & Ahn, Hyun-Soo, 2011. "Joint management of capacity and inventory in make-to-stock production systems with multi-class demand," European Journal of Operational Research, Elsevier, vol. 212(2), pages 312-324, July.
    4. Albert Y. Ha, 1997. "Inventory Rationing in a Make-to-Stock Production System with Several Demand Classes and Lost Sales," Management Science, INFORMS, vol. 43(8), pages 1093-1103, August.
    5. Li, Haitao & Womer, Keith, 2012. "Optimizing the supply chain configuration for make-to-order manufacturing," European Journal of Operational Research, Elsevier, vol. 221(1), pages 118-128.
    6. Chiu, Singa Wang, 2008. "Production lot size problem with failure in repair and backlogging derived without derivatives," European Journal of Operational Research, Elsevier, vol. 188(2), pages 610-615, July.
    7. Wedad Elmaghraby & P{i}nar Keskinocak, 2003. "Dynamic Pricing in the Presence of Inventory Considerations: Research Overview, Current Practices, and Future Directions," Management Science, INFORMS, vol. 49(10), pages 1287-1309, 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. Diaz, Juan Esteban & Handl, Julia & Xu, Dong-Ling, 2018. "Integrating meta-heuristics, simulation and exact techniques for production planning of a failure-prone manufacturing system," European Journal of Operational Research, Elsevier, vol. 266(3), pages 976-989.
    2. Christian Finnsgård & Joakim Kalantari & Zeeshan Raza & Violeta Roso & Johan Woxenius, 2018. "Swedish shippers’ strategies for coping with slow-steaming in deep sea container shipping," Journal of Shipping and Trade, Springer, vol. 3(1), pages 1-24, December.
    3. Sobhani, A. & Wahab, M.I.M. & Neumann, W.P., 2017. "Incorporating human factors-related performance variation in optimizing a serial system," European Journal of Operational Research, Elsevier, vol. 257(1), pages 69-83.
    4. Barış Tan, 2019. "Production Control with Price, Cost, and Demand Uncertainty," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 41(4), pages 1057-1085, December.

    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. Hossein Abouee-Mehrizi & Barış Balcıoğlu & Opher Baron, 2012. "Strategies for a Centralized Single Product Multiclass M/G/ 1 Make-to-Stock Queue," Operations Research, INFORMS, vol. 60(4), pages 803-812, August.
    2. Secil Savasaneril & Ece Sayin, 2017. "Dynamic lead time quotation under responsive inventory and multiple customer classes," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 95-135, January.
    3. Elhafsi, Mohsen & Hamouda, Essia, 2018. "Managing an integrated production and inventory system selling to a dual market: Long-term and walk-in," European Journal of Operational Research, Elsevier, vol. 268(1), pages 215-230.
    4. Hung, Yi-Feng & Lee, Tzu-Yuan, 2010. "Capacity rationing decision procedures with order profit as a continuous random variable," International Journal of Production Economics, Elsevier, vol. 125(1), pages 125-136, May.
    5. Ozgun Caliskan Demirag & Ozgul Baysar & Pinar Keskinocak & Julie L. Swann, 2010. "The effects of customer rebates and retailer incentives on a manufacturer's profits and sales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 57(1), pages 88-108, February.
    6. Vincent Mak & Amnon Rapoport & Eyran J. Gisches & Jiaojie Han, 2014. "Purchasing Scarce Products Under Dynamic Pricing: An Experimental Investigation," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 425-438, July.
    7. Gökçe Kahveciog̃lu & Barış Balcıog̃lu, 2016. "Coping with production time variability via dynamic lead-time quotation," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 38(4), pages 877-898, October.
    8. Benny Mantin & Daniel Granot & Frieda Granot, 2011. "Dynamic pricing under first order Markovian competition," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(6), pages 608-617, September.
    9. Zhao, Ju & Qiu, Ju & Zhou, Yong-Wu & Hu, Xiao-Jian & Yang, Ai-Feng, 2020. "Quality disclosure in the presence of strategic consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    10. Alarcón, F. & Alemany, M.M.E. & Ortiz, A., 2009. "Conceptual framework for the characterization of the order promising process in a collaborative selling network context," International Journal of Production Economics, Elsevier, vol. 120(1), pages 100-114, July.
    11. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2017. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Working Papers hal-01592958, HAL.
    12. Dasci, A. & Karakul, M., 2009. "Two-period dynamic versus fixed-ratio pricing in a capacity constrained duopoly," European Journal of Operational Research, Elsevier, vol. 197(3), pages 945-968, September.
    13. Vincent Mak & Amnon Rapoport & Eyran J. Gisches, 2018. "Dynamic Pricing Decisions and Seller-Buyer Interactions under Capacity Constraints," Games, MDPI, Open Access Journal, vol. 9(1), pages 1-23, February.
    14. Satır, Benhür & Erenay, Fatih Safa & Bookbinder, James H., 2018. "Shipment consolidation with two demand classes: Rationing the dispatch capacity," European Journal of Operational Research, Elsevier, vol. 270(1), pages 171-184.
    15. Shone, Rob & Glazebrook, Kevin & Zografos, Konstantinos G., 2019. "Resource allocation in congested queueing systems with time-varying demand: An application to airport operations," European Journal of Operational Research, Elsevier, vol. 276(2), pages 566-581.
    16. Dong Li & Xiaojun Wang, 2017. "Dynamic supply chain decisions based on networked sensor data: an application in the chilled food retail chain," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5127-5141, September.
    17. Hayya, Jack C. & Harrison, Terry P. & He, X. James, 2011. "The impact of stochastic lead time reduction on inventory cost under order crossover," European Journal of Operational Research, Elsevier, vol. 211(2), pages 274-281, June.
    18. Long Gao & Susan H. Xu & Michael O. Ball, 2012. "Managing an Available-to-Promise Assembly System with Dynamic Short-Term Pseudo-Order Forecast," Management Science, INFORMS, vol. 58(4), pages 770-790, April.
    19. Xuejie Bai & Yankui Liu, 2016. "Robust optimization of supply chain network design in fuzzy decision system," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1131-1149, December.
    20. Chenavaz, Régis & Paraschiv, Corina, 2018. "Dynamic pricing for inventories with reference price effects," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy (IfW), vol. 12, pages 1-16.

    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:ejores:v:238:y:2014:i:1:p:122-129. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nithya Sathishkumar). General contact details of provider: http://www.elsevier.com/locate/eor .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.