Diseño de un modelo matemático de reaprovisionamiento de la categoría bebidas no alcohólicas para una cadena de tiendas de conveniencias

Abstract

CONDITION FOR PUBLICATION OF PROJECT. The present study focuses on the design of a mathematical replenishment model aimed at optimizing inventory management for non-alcoholic beverages in a convenience store chain in Ecuador. The research is based on the analysis of stockouts and overstocking issues, which negatively affect profitability and product availability. The objective is to develop a stochastic model, leveraging time series analysis and mixed-integer linear programming, to minimize operational costs and enhance logistical efficiency. The methodology involves the collection and analysis of three years of historical sales data, identification of demand patterns, and scenario simulations using Monte Carlo techniques. The findings indicate that the implementation of the model optimizes inventory replenishment, ensuring a service level exceeding 95% and reducing obsolescence-related losses by up to 8%. The study concludes that integrating predictive models into the supply chain facilitates more efficient management and provides greater adaptability to demand variability, thereby contributing to operational sustainability and customer satisfaction. KEYWORDS: inventory management, logistics optimization, stochastic model, replenishment, uncertain demand.