IDEAS home Printed from https://ideas.repec.org/a/spr/opmare/v14y2021i1d10.1007_s12063-021-00191-2.html
   My bibliography  Save this article

The average-cost formulation of lot sizing models and inventory carrying charges: a technical note

Author

Listed:
  • Davide Castellano

    (Università degli Studi di Napoli “Federico II”)

  • Christoph H. Glock

    (Technical University of Darmstadt)

Abstract

It is generally recognised that the present-value criterion should be preferred to the average-cost formulation in developing lot sizing models. Despite the advantages of the present-value measure, average-cost lot sizing models are far more widely applied. Because of the nature of the average-cost formulation, inventory carrying costs are evaluated according to a look-back approach, relying on historical values. In this regard, a general misconception in the inventory management literature concerned with average-cost models is that the unit stockholding cost rate should be established considering fixed warehouse costs, which are costs that are, in the short term, independent of the inventory level. This paper develops arguments supporting our belief that inventory carrying charges used in lot sizing models should take into account only those costs varying with the inventory level in the warehouse, and that considering fixed warehouse costs leads to pitfalls when making inventory replenishment decisions. To this aim, we first present an analytical treatment based on the classical Economic Order Quantity (EOQ) model, as its full analytical tractability permits us to better discuss the problem we are interested in. Finally, we present numerical experiments to assess the effect of the correct procedure to establish the unit stockholding cost rate on inventory management decisions. These experiments are performed considering warehouse costs taken from some industrial case studies presented in the literature.

Suggested Citation

  • Davide Castellano & Christoph H. Glock, 2021. "The average-cost formulation of lot sizing models and inventory carrying charges: a technical note," Operations Management Research, Springer, vol. 14(1), pages 194-201, June.
  • Handle: RePEc:spr:opmare:v:14:y:2021:i:1:d:10.1007_s12063-021-00191-2
    DOI: 10.1007/s12063-021-00191-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12063-021-00191-2
    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/s12063-021-00191-2?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. Andriolo, Alessandro & Battini, Daria & Grubbström, Robert W. & Persona, Alessandro & Sgarbossa, Fabio, 2014. "A century of evolution from Harris׳s basic lot size model: Survey and research agenda," International Journal of Production Economics, Elsevier, vol. 155(C), pages 16-38.
    2. Glock, C. H., 2014. "Produktion und Supply Chain Management. Eine Einführung," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 66208, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Glock, Christoph H. & Grosse, Eric H. & Ries, Jörg M., 2014. "The lot sizing problem: A tertiary study," International Journal of Production Economics, Elsevier, vol. 155(C), pages 39-51.
    4. Teunter, Ruud H. & van der Laan, Erwin & Inderfurth, Karl, 2000. "How to set the holding cost rates in average cost inventory models with reverse logistics?," Omega, Elsevier, vol. 28(4), pages 409-415, August.
    5. Grubbstrom, Robert W. & Thorstenson, Anders, 1986. "Evaluation of capital costs in a multi-level inventory system by means of the annuity stream principle," European Journal of Operational Research, Elsevier, vol. 24(1), pages 136-145, January.
    6. Glock, C. H. & Grosse, E. H. & Ries, J. M., 2014. "The Lot Sizing Problem: A Tertiary Study," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63361, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    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. Debabrata Das & Sameer Kumar & Nirmal Baran Hui & Vipul Jain & Charu Chandra, 2023. "Pricing and revenue-based outsourcing strategies in a multi-echelon lot-sizing model under insufficient production capacity," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 22(6), pages 514-530, December.
    2. Parisa Rafigh & Ali Akbar Akbari & Hadi Mohammadi Bidhandi & Ali Husseinzadeh Kashan, 2022. "A sustainable supply chain network considering lot sizing with quantity discounts under disruption risks: centralized and decentralized models," Journal of Combinatorial Optimization, Springer, vol. 44(3), pages 1387-1432, October.

    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. Battini, Daria & Glock, Christoph H. & Grosse, Eric H. & Persona, Alessandro & Sgarbossa, Fabio, 2017. "Reprint of “Ergo-lot-sizing: An approach to integrate ergonomic and economic objectives in manual materials handling”," International Journal of Production Economics, Elsevier, vol. 194(C), pages 32-42.
    2. Hovelaque, Vincent & Bironneau, Laurent, 2015. "The carbon-constrained EOQ model with carbon emission dependent demand," International Journal of Production Economics, Elsevier, vol. 164(C), pages 285-291.
    3. Prasert Aengchuan & Busaba Phruksaphanrat, 2018. "Comparison of fuzzy inference system (FIS), FIS with artificial neural networks (FIS + ANN) and FIS with adaptive neuro-fuzzy inference system (FIS + ANFIS) for inventory control," Journal of Intelligent Manufacturing, Springer, vol. 29(4), pages 905-923, April.
    4. Glock, Christoph H. & Grosse, Eric H., 2021. "The impact of controllable production rates on the performance of inventory systems: A systematic review of the literature," European Journal of Operational Research, Elsevier, vol. 288(3), pages 703-720.
    5. Pilar I. Vidal-Carreras & Jose P. Garcia-Sabater & Julio J. Garcia-Sabater, 2017. "A practical model for managing inventories with unknown costs and a budget constraint," International Journal of Production Research, Taylor & Francis Journals, vol. 55(1), pages 118-129, January.
    6. Melega, Gislaine Mara & de Araujo, Silvio Alexandre & Jans, Raf, 2018. "Classification and literature review of integrated lot-sizing and cutting stock problems," European Journal of Operational Research, Elsevier, vol. 271(1), pages 1-19.
    7. Corbacioglu, Umut & van der Laan, Erwin A., 2007. "Setting the holding cost rates in a two-product system with remanufacturing," International Journal of Production Economics, Elsevier, vol. 109(1-2), pages 185-194, September.
    8. Menezes, Mozart B.C. & Jalali, Hamed & Lamas, Alejandro, 2021. "One too many: Product proliferation and the financial performance in manufacturing," International Journal of Production Economics, Elsevier, vol. 242(C).
    9. Avelina Alejo-Reyes & Erik Cuevas & Alma Rodríguez & Abraham Mendoza & Elias Olivares-Benitez, 2020. "An Improved Grey Wolf Optimizer for a Supplier Selection and Order Quantity Allocation Problem," Mathematics, MDPI, vol. 8(9), pages 1-24, August.
    10. Quetschlich, Mathias & Moetz, André & Otto, Boris, 2021. "Optimisation model for multi-item multi-echelon supply chains with nested multi-level products," European Journal of Operational Research, Elsevier, vol. 290(1), pages 144-158.
    11. Oliveira, Washington A. & Fiorotto, Diego J. & Song, Xiang & Jones, Dylan F., 2021. "An extended goal programming model for the multiobjective integrated lot-sizing and cutting stock problem," European Journal of Operational Research, Elsevier, vol. 295(3), pages 996-1007.
    12. Beullens, Patrick, 2014. "Revisiting foundations in lot sizing—Connections between Harris, Crowther, Monahan, and Clark," International Journal of Production Economics, Elsevier, vol. 155(C), pages 68-81.
    13. Mac Cawley, Alejandro & Maturana, Sergio & Pascual, Rodrigo & Tortorella, Guilherme Luz, 2022. "Scheduling wine bottling operations with multiple lines and sequence-dependent set-up times: Robust formulation and a decomposition solution approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 819-839.
    14. S. Priyan & R. Uthayakumar, 2017. "Setup cost reduction EMQ inventory system with probabilistic defective and rework in multiple shipments management," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 223-241, June.
    15. Lucio Enrico Zavanella & Beatrice Marchi & Simone Zanoni & Ivan Ferretti, 2019. "Energy considerations for the economic production quantity and the joint economic lot sizing," Journal of Business Economics, Springer, vol. 89(7), pages 845-865, September.
    16. Bensmain, Yassir & Dahane, Mohammed & Bennekrouf, Mohammed & Sari, Zaki, 2019. "Preventive remanufacturing planning of production equipment under operational and imperfect maintenance constraints: A hybrid genetic algorithm based approach," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 546-566.
    17. Jafari, L. & Makis, V., 2015. "Joint optimal lot sizing and preventive maintenance policy for a production facility subject to condition monitoring," International Journal of Production Economics, Elsevier, vol. 169(C), pages 156-168.
    18. Ghiami, Yousef, 2023. "An analysis on production and inventory models with discounted cash-flows," Omega, Elsevier, vol. 117(C).
    19. Kim, Taebok & Glock, Christoph H., 2018. "Production planning for a two-stage production system with multiple parallel machines and variable production rates," International Journal of Production Economics, Elsevier, vol. 196(C), pages 284-292.
    20. Sahling, Florian & Hahn, Gerd J., 2019. "Dynamic lot sizing in biopharmaceutical manufacturing," International Journal of Production Economics, Elsevier, vol. 207(C), pages 96-106.

    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:opmare:v:14:y:2021:i:1:d:10.1007_s12063-021-00191-2. 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.