Context of the inventory management expenses in the case of planned shortages

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The main purpose of the paper is to present the relations between the different cost factors of the inventory management systems, and the context between the order quantities and the cost level. The theoretical approach of the model assumes a deterministic operational environment with planned shortages. We make the examination of the contexts by applying the ceteris paribus principle; we change only one cost factor from among the initial conditions at once and examine its effect on the cost level.

By using the economic order quantity with the planned shortage model, we can define the optimal order quantity, along which our stock management can be guaranteed by the most favourable cost level. The optimisation of the inventory level and the inventory management expenses together means an important factor in the competitiveness of the company. During the definition of the optimal inventory level of purchased parts, the purchasing and stock holding costs, and also the consequence of shortages play an important role. The presentation of the specific expense factors in each other’s function, and the representation of the onetime order expenses show their proportion compared to each other and the effect of their change on the total cost, and define the opportunities of the optimisation. The significance of the model is that it represents the level line of costs, the movement of the different cost factors in relation to others and their operating mechanism. Thus, it facilitates the representation of costs and the definition of the direction of optimisation.


  • Böventer, E. (1991). Einführung in die Mikroökonomie [Introduction in to microeconomics]. München, Germany: R. Oldenbourg Verlag GmbH.

  • Cárdenas-Barrón, L. E. (2010). A simple method to compute economic order quantities: Some observations. Applied Mathematical Modelling, 34, 1684-1688.

  • Chang, H. J., & Dye, C. Y. (1999). An EOQ model for deteriorating items with time varying demand and partial backlogging. Journal of the Operational Research Society, 50, 1176-1182.

  • Chopra, S., & Meindl, P. (2007). Supply Chain Management Strategy, Planning and Operation, 3rd Edition. New York, USA: Pearson Prentice-Hall Publishers.

  • Dave, U. (1989). On a heuristic inventory-replenishment rule for items with a linearly increasing demand incorporating shortages. Journal of the Operational Research Society, 38, 459-463.

  • Deb, M., & Chaudhuri, K. S. (1987). A note on the heuristic for replenishment of trended inventories considering shortages. Journal of Operational Research Society, 38, 459-463.

  • Eroglu, A., & Ozdemir, G. (2007). An economic order quantity model with defective items and shortages. International Journal of Production Economics, 106, 544-549.

  • Ghare, P. M., & Schrader, G. F. (1963). A model for an exponentially decaying inventory. Journal of Industrial Engineering, 14, 238-243.

  • Grubbström, R. W., & Erdem, A. (1999). EOQ with backlogging derived without derivatives. International Journal of Production Economics, 59, 529-530.

  • Halászné, S. E. (1998). Logisztika, szolgáltatások, versenyképesség [Logistics – services, competitiveness]. Budapest, Hungary: Magyar Világ Kiadó.

  • Harris, F. W. (1913). How Many Parts to Make at Once, Factory. The Magazine of Management, 10, 135-136, 152.

  • Hollier, R. H., & Mak, K. L. (1983). Inventory replenishment policies for deteriorating items in a declining market. International Journal of Production Research, 21, 813-826.

  • Huang, B., & Wu, A. (2016). EOQ model with batch demand and planned backorders. Applied Mathematical Modelling, 40(9–10), 5482-5496.

  • Illés, I. (1998). Társaságok pénzügyei [Companies’ financial affairs]. Budapest, Hungary: SALDO Kiadó.

  • Jaynes, E. T. (2003). Probability theory: The logic of science. Cambridge, Great Britain: Cambridge University Press.

  • Koltai, T. (2009). Termelésmenedzsment [Production Management]. Budapest, Hungary: Typotex Kiadó.

  • Kopányi, M. (1996). Mikroökonómia [Microeconomics]. Budapest, Hungary: Műszaki Könyvkiadó.

  • Krampe, H., Lucke, H-J., & Schenk, M. (2012). Grundlagen der Logistik [Basics of logistics]. München, Germany: Huss-Verlag GmbH.

  • Kulcsár, B. (1998). Ipari logisztika [Industrial logistics]. Budapest, Hungary: LSI Oktatóközpont.

  • Kummer, S., Grün, O., & Jammernegg, W. (2009). Grundzüge der Beschaffung, Produktion und Logistik [Basics of purchasing, production, logistics]. München, Germany: Pearson Studium, München.

  • Paknejad, J., Nasri, F., & Affisco, J. F. (2015). Yield improvement and yield variability reduction in an EOQ model with planned shortages and random yield. Computers & Industrial Engineering, 88, 386-394.

  • Park, K. S. (1982). Inventory models with partial backorders. International Journal of Systems Science, 13, 1313-1317.

  • Porteus, E. L. (1986). Optimal lot sizing, process quality improvement and setup cost reduction. Operations Research, 34(1), 137-144.

  • Salameh, M. K., & Jaber, M. Y. (2000). Economic production quantity model for items with imperfect quality. International Journal of Production Economics, 64, 59-64.

  • Stock, J. R., & Lambert, D. M. (2001). Strategic Logistics Management. Boston, USA: McGraw-Hill Higher Education.

  • Szegedi, Z., & Prezenszki, J. (2003). Logisztika-menedzsment [Logistics Management]. Budapest, Hungary: Kossuth Kiadó.

  • Teng, J. T., & Yang, H. L. (2004). Deterministic economic order quantity models with partial backlogging when demand and cost are fluctuating with time. Journal of the Operational Research Society, 55, 495-503.

  • Tersine, R., & Barman, S. (1991). Lot size optimization with quantity and freight rate discounts. Logistics and Transportation Review, 27(4), 319-332.

  • Vijayan, T., & Kumaran, M. (2009). Fuzzy economic order time models with random demand. International Journal of Approximate Reasoning, 50(3), 529-540.

  • Vörös, J. (1991). Termelés management [Production Management]. Pécs, Hungary: Jannus Pannonius Kiadó.

  • Vörös, J. (2010). Termelés- és szolgáltatásmenedzsment [Production and service management]. Budapest, Hungary: Akadémia Kiadó.

  • Wagner, H. M., & Whitin, T. M. (1958). Dynamic version of the economic lot size model. Management Science, 5(1), 89-96.

  • Wee, H. M., Yu, J. C. P., & Wang, K. J. (2006). An integrated production inventory model for deteriorating items with imperfect quality and shortage backordering considerations. Lecture Notes in Computer Science, 3982, 885-897.

  • Wee, H. M., Yu, J., & Chen, M. C. (2007). Optimal inventory model for items with imperfect quality and shortage backordering. Omega, 35, 7-11.

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