Inventory lot-size policies for deteriorating items with expiration dates and advance payments

• Published in: Applied mathematical modelling Vol. 40; no. 19-20; pp. 8605 - 8616
• Main Authors: Teng, Jinn-Tsair, Cárdenas-Barrón, Leopoldo Eduardo, Chang, Horng-Jinh, Wu, Jiang, Hu, Yihang
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01-10-2016
• Subjects: Advance payments; Deteriorating items; Expiration dates; Finance; Inventory; Deteriorating items; Expiration dates; Advance payments; Finance; Inventory
• ISSN: 0307-904X
• DOI: 10.1016/j.apm.2016.05.022

•Proposes an inventory model for deteriorating items with expiration dates and advance payments.•The retailer’s decision variables are the cycle time and the fraction of no shortages.•It is shown that the total cost is strictly pseudo-convex in either one of two decision variables.•The paper provides an optimal solution for arbitrary deterioration rates.•Some managerial insights are presented.
For deteriorating items with seasonal demand, a supplier usually requests that the buyer (retailer) prepays a fraction of the acquisition cost as a deposit. The expiration date of a deteriorating item is an important factor in a buyer's purchase decision. Despite its importance, relatively little attention has been paid to the effects of the expiration date; the versions of economic order quantity models that are available consider fixed deterioration rates. This paper considers a more realistic situation where the deterioration rate of a product gradually increases as the expiration date approaches. In this paper, the optimal cycle time and the cycle fraction of no shortages are the decision variables that minimize the total cost. The total annual relevant cost is shown to be strictly pseudo-convex for each of the decision variables, which simplifies the search for the global solution to a local minimum. This paper provides an improvement on earlier work, as it provides an optimal rather than a near-optimal solution. Several numerical examples are provided to illustrate the behaviour of the model and to highlight some managerial insights.