Optimizing Traceability in the Meat Supply Chain

Abstract

Over the past decades, several measures have been taken to solve the different public health problems caused by food. Among them, the traceability is one of outstanding importance, which allows tracking and tracing products efficiently. The objective of this work is to minimize the total dispersion of production batches in the supply chain of meat products in order to optimize their traceability. To do so, a mixed integer linear programming (MILP) model is developed, whose decision variables are employed to determine the existence of batches and their number at each node, their quantities, and the involved actors. The results show that an optimal number of batches can be produced and their dispersion diminished, which in turn allows minimizing the costs of possible product recalls in the case of a food safety incident. In addition, the formulation allows tracing the product batches at each node of the supply chain, identifying the batches of animals and raw materials utilized in their production.