Inventory Management with Continuous Review Model and Seasonal Demand
DOI:
https://doi.org/10.56368/Entrelineas426Keywords:
Probabilistic models, inventory management, continuous review, economic order quantityAbstract
Efficient inventory management is a constant challenge for companies operating with variable demand. Probabilistic models with continuous review are an effective tool for anticipating needs and reducing costs. The objective of this study was to evaluate the effectiveness of a probabilistic inventory model with independent demand and continuous review, applied to a chocolate retailer, in order to optimize order quantity and reorder point. The research was based on theoretical references such as Taha, Hillier, and Lieberman, as well as Hadley and Whitin, who developed the fundamentals of stochastic models used in inventory management. The methodology used a quantitative and applied approach, analyzing historical sales data from Chocolaterías Milkaelos, focusing on the five most demanded products, and comparing deterministic and probabilistic (EOQ) models considering seasonal variability in demand. The results showed that the probabilistic model allowed for more accurate prediction of optimal order quantities and reorder points, adjusting for seasonal changes and reducing storage and stockout costs. In conclusion, the continuous review model is established as an effective tool for balancing, strengthening, and managing inventory.
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