Integrating Efficiency and Sustainability in Optimizing Milk Collection Logistics

Abstract

Milk collection in the Argentine dairy industry is largely managed manually, despite technological advances. This work proposes an optimization model based on the vehicle routing problem (VRP) with a heterogeneous fleet. This model incorporates not only the distance traveled but also the load transported, allowing for more accurate estimates of carbon dioxide emissions. A variant of the simulated annealing algorithm generates efficient routes under capacity constraints and variable demands. The optimal solutions obtained by minimizing the total distance are compared with those that minimize carbon dioxide emissions. The results show that minimizing distance does not always imply minimizing emissions, highlighting the need for solutions that balance logistical efficiency and environmental impact, especially in the Pampas region, where the distances between dairy farms and processing plants are long. The proposed methodology represents an advance over previous studies by simultaneously integrating distance, load, and emissions, with an approach applicable to the daily planning of dairy industries in Argentina.