Optimal Ordering Policies for Supermarkets under Static Pricing and Stochastic Demand: A Case Study of Milk Powder Product

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dc.contributor.authorMubiru, Kizito Paul
dc.contributor.authorBuhwezi, Bernard Kariko
dc.contributor.authorLating, Peter Okidi
dc.date.accessioned2022-01-23T11:58:17Z
dc.date.available2022-01-23T11:58:17Z
dc.date.issued2013
dc.description.abstractDemand uncertainty affects a significant portion of sales revenue in supermarkets. In this paper, we develop a new approach to formulate and optimize the single-item, finite horizon, periodic review revenue problem of milk powder product under stochastic demand. A special case of our model is where sales price and scheduled inventory replenishment periods are uniformly fixed at all supermarkets. Adopting a Markov decision process approach, the states of a Markov chain represent possible states of demand for milk powder product. The decision of whether or not to order additional units is made using dynamic programming over a finite period planning horizon. Numerical results demonstrate the existence of an optimal state-dependent ordering policy and the corresponding sales revenue of milk powder product in supermarkets.en_US
dc.identifier.citationMubiru, K. P., KarikoBuhwezi, B., & Lating, P. O. Optimal Ordering Policies for Supermarkets under Static Pricing and Stochastic Demand: A Case Study of Milk Powder Product.en_US
dc.identifier.issn2278 – 0882
dc.identifier.urihttps://nru.uncst.go.ug/xmlui/handle/123456789/1461
dc.language.isoenen_US
dc.publisherInternational Journal of Scientific Research Engineering & Technologyen_US
dc.subjectOptimization, ordering policies, static pricing, stochastic demanden_US
dc.titleOptimal Ordering Policies for Supermarkets under Static Pricing and Stochastic Demand: A Case Study of Milk Powder Producten_US
dc.typeArticleen_US
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