Single item inventory control under periodic review and a minimum order quantity
AbstractIn this paper we study a periodic review single item single stage inventory system with stochastic demand. In each time period the system must order none or at least as much as a minimum order quantity Qmin. Since the optimal structure of an ordering policy with a minimum order quantity is complicated, we propose an easy-to-use policy, which we call (R, S, Qmin) policy. Assuming linear holding and backorder costs we determine the optimal numerical value of the level S using a Markov Chain approach. In addition, we derive simple news-vendor-type inequalities for near-optimal policy parameters, which can easily be implemented within spreadsheet applications. In a numerical study we compare our policy with others and test the performance of the approximation for three different demand distributions: Poisson, negative binomial, and a discretized version of the gamma distribution. Given the simplicity of the policy and its cost performance as well as the excellent performance of the approximation we advocate the application of the (R, S, Qmin) policy in practice.
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Bibliographic InfoArticle provided by Elsevier in its journal International Journal of Production Economics.
Volume (Year): 133 (2011)
Issue (Month): 1 (September)
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Web page: http://www.elsevier.com/locate/ijpe
Stochastic inventory model Minimum order quantity Markov Chain News-vendor inequality;
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Zhou, Bin & Zhao, Yao & Katehakis, Michael N., 2007. "Effective control policies for stochastic inventory systems with a minimum order quantity and linear costs," International Journal of Production Economics, Elsevier, vol. 106(2), pages 523-531, April.
- Ho, Jyh-Wen & Fang, Chih-Chiang, 2013. "Production capacity planning for multiple products under uncertain demand conditions," International Journal of Production Economics, Elsevier, vol. 141(2), pages 593-604.
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