Optimal contribution margin in food service using inventory control with statistical dependence

Abstract

In this review we compared different statistical modeling that optimize the contribution margins of food services companies that produce food rations called menus based on raw materials denominated components. This review aims to compare inventory control for food services considering random demand and structure dependence regarding independent demands of the components. The statistical dependence between demands for components or menus is incorporated by Gaussian (or normal) distribution multivariate, while independent demand for components is considered normal univariate. Optimization of contribution margins is achieved using probabilistic models for each component inventories and finding optimal policies by the differential evolution algorithm. We maximize average contribution margins in an 18.32% and 8.34% using models of continuous review for groceries and single-period for perishable components with and without statistical dependence on demand, respectively. Future directions are discussed.