Inventory Optimization Model for Deteriorating Items under Inventory Follows Shortage (IFS) and Shortage Follows Inventory (SFI) Policies
DOI:
https://doi.org/10.26713/cma.v15i3.2829Keywords:
SFI policy, IFS policy, Allowed shortages, Complete backlog, Permissible delay in payment, Preservation technologyAbstract
This study focuses on optimizing inventory control for perishable commodities using preservation technologies, where payment delays and shortages are acceptable. Implementing correct preservation technology can help retailers reduce the negative impact of product deterioration on their earnings. We examine preservation technology as well as the permitted payment delay and aim to minimize the total cost under two different policies: SFI and IFS. The flow of inventory is quantitatively described for both policies using dynamic differential equations and the necessary boundary conditions. The decision variables’ values are determined using the derivative method of calculus. Furthermore, the optimum values of the Total cost function satisfy the Hessian matrix requirement, confirming its convexity. Based on all the results of the study we compare both the models for optimum Total Cost and found out the most and least affecting parameters for this model. The key finding of this study is the comparison of these models under two different policies to identify which policy is better to minimize the total cost for the retailers. We observed that IFS performs well to optimize the total cost. Numerical examples are also provided to show the practical use of the proposed model. Given the presence of preservation technology, we observed that the total cost in IFS policy is 6.81% higher than that of the case when it is absent, whereas in SFI the total cost is 5.29% higher than when it is not there. A table showing the effect of various parameters on the total cost function is provided and subsequent insights that are beneficial for retailers are also drawn and some unanswered queries are the highlights of this problem.
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