IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v58y2021i1d10.1007_s12597-020-00471-8.html
   My bibliography  Save this article

A production inventory model with deteriorating items and retrial demands

Author

Listed:
  • K. P. Jose

    (St. Peter’s College)

  • P. S. Reshmi

    (St. Peter’s College)

Abstract

This paper considers a single server perishable inventory system in which customers arrive in a homogeneous Poisson stream. The system has a production unit which produces a single item in an exponentially distributed time interval. At the time of arrival, a customer leads to service if the server is available with a positive level of inventory. Otherwise, the customer goes to a waiting place(orbit) of infinite capacity with pre-determined probability or exits the system with complementary probability. Each customer in the orbit tries to access the server in an exponentially distributed time interval. After every unsuccessful retrial, the customer returns to the orbit with a pre-allotted probability or is lost forever with complementary probability. An algorithmic solution to the problem is obtained using Matrix Analytic Method. The mean number of customer loss before and after entering the system, the rate of successful retrials among overall retrials and some other performance measures of the system are derived. The impacts of system parameters on different measures are numerically studied. A suitable cost function is constructed and the optimum control policy is numerically obtained.

Suggested Citation

  • K. P. Jose & P. S. Reshmi, 2021. "A production inventory model with deteriorating items and retrial demands," OPSEARCH, Springer;Operational Research Society of India, vol. 58(1), pages 71-82, March.
    • Handle: RePEc:spr:opsear:v:58:y:2021:i:1:d:10.1007_s12597-020-00471-8
    DOI: 10.1007/s12597-020-00471-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-020-00471-8
    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/s12597-020-00471-8?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Steven Nahmias, 1982. "Perishable Inventory Theory: A Review," Operations Research, INFORMS, vol. 30(4), pages 680-708, August.
    2. 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.
    3. Krishnamoorthy, A. & Viswanath, Narayanan C., 2013. "Stochastic decomposition in production inventory with service time," European Journal of Operational Research, Elsevier, vol. 228(2), pages 358-366.
    4. P. Vijaya Laxmi & M.L. Soujanya, 2018. "Perishable inventory model with Markovian arrival process, retrial demands and multiple working vacations," International Journal of Inventory Research, Inderscience Enterprises Ltd, vol. 5(2), pages 79-98.
    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. V. Radhamani & B. Sivakumar & G. Arivarignan, 2022. "A Comparative Study on Replenishment Policies for Perishable Inventory System with Service Facility and Multiple Server Vacation," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 229-265, March.
    2. Ketzenberg, M.E. & Bloemhof-Ruwaard, J.M., 2009. "The Value of RFID Technology Enabled Information to Manage Perishables," ERIM Report Series Research in Management ERS-2009-020-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    3. Lodree Jr., Emmett J. & Uzochukwu, Benedict M., 2008. "Production planning for a deteriorating item with stochastic demand and consumer choice," International Journal of Production Economics, Elsevier, vol. 116(2), pages 219-232, December.
    4. 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.
    5. Li‐Ming Chen & Amar Sapra, 2013. "Joint inventory and pricing decisions for perishable products with two‐period lifetime," Naval Research Logistics (NRL), John Wiley & Sons, vol. 60(5), pages 343-366, August.
    6. Omar Ahumada & J. Villalobos, 2011. "A tactical model for planning the production and distribution of fresh produce," Annals of Operations Research, Springer, vol. 190(1), pages 339-358, October.
    7. R Bai & E K Burke & G Kendall, 2008. "Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1387-1397, October.
    8. Rong, Aiying & Akkerman, Renzo & Grunow, Martin, 2011. "An optimization approach for managing fresh food quality throughout the supply chain," International Journal of Production Economics, Elsevier, vol. 131(1), pages 421-429, May.
    9. J-M Chen & L-T Chen, 2004. "Pricing and lot-sizing for a deteriorating item in a periodic review inventory system with shortages," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 892-901, August.
    10. Yadavalli, V.S.S. & Sivakumar, B. & Arivarignan, G., 2008. "Inventory system with renewal demands at service facilities," International Journal of Production Economics, Elsevier, vol. 114(1), pages 252-264, July.
    11. Guowei Liu & Jianxiong Zhang & Wansheng Tang, 2015. "Joint dynamic pricing and investment strategy for perishable foods with price-quality dependent demand," Annals of Operations Research, Springer, vol. 226(1), pages 397-416, March.
    12. Feng, Lin & Wang, Wan-Chih & Teng, Jinn-Tsair & Cárdenas-Barrón, Leopoldo Eduardo, 2022. "Pricing and lot-sizing decision for fresh goods when demand depends on unit price, displaying stocks and product age under generalized payments," European Journal of Operational Research, Elsevier, vol. 296(3), pages 940-952.
    13. Sandun C. Perera & Suresh P. Sethi, 2023. "A survey of stochastic inventory models with fixed costs: Optimality of (s, S) and (s, S)‐type policies—Discrete‐time case," Production and Operations Management, Production and Operations Management Society, vol. 32(1), pages 131-153, January.
    14. Li‐Ming Chen & Amar Sapra, 2021. "Inventory renewal for a perishable product: Economies of scale and age‐dependent demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 68(3), pages 359-377, April.
    15. Li, Jian & Edwin Cheng, T.C. & Wang, Shouyang, 2007. "Analysis of postponement strategy for perishable items by EOQ-based models," International Journal of Production Economics, Elsevier, vol. 107(1), pages 31-38, May.
    16. Castellano, Davide & Glock, Christoph H., 2024. "Economic production quantity for a decaying item with stochastic demand and positive lead time," International Journal of Production Economics, Elsevier, vol. 267(C).
    17. Tara Rengarajan & Nedialko Dimitrov & David P. Morton, 2013. "Convex Approximations of a Probabilistic Bicriteria Model with Disruptions," INFORMS Journal on Computing, INFORMS, vol. 25(1), pages 147-160, February.
    18. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    19. Onur Kaya & Aylin Lelizar Polat, 2017. "Coordinated pricing and inventory decisions for perishable products," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(2), pages 589-606, March.
    20. Tal Avinadav & Tatyana Chernonog & Yael Lahav & Uriel Spiegel, 2017. "Dynamic pricing and promotion expenditures in an EOQ model of perishable products," Annals of Operations Research, Springer, vol. 248(1), pages 75-91, January.

    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:opsear:v:58:y:2021:i:1:d:10.1007_s12597-020-00471-8. 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.