A mixed integer linear programming approach for the optimization of food traceability logistics

A traceability system rigorously collects all the information related to a specific product along the supply chain. This information will be essential to face a food safety crisis and manage the consequently product recall action. Although a recall could be absolutely critical for a company – both for the costs and the media impact-, at present, most companies do not have reliable methods to precisely estimate the amount of product that would be discarded in the case of a recall. The skill to hold this quantity down can be assumed as a measure of the performance and of the efficiency of the traceability system adopted by the company. This paper introduces novel criteria and methodologies for measuring and optimizing the performance of a traceability system. As opposed to previous introduced methods, which optimize indirect measures, the proposed approach takes in direct account the total (or the worst-case) quantity of product that should be recalled in the case of a crisis. Some numerical examples concerning the mixing of batches in a sausage production process are reported to show the effectiveness of the proposed approach.