Optimizing the Organization of the First Mile in Agri-Food Supply Chains with a Heterogeneous Fleet Using a Mixed-Integer Linear Model

Abstract

Consumers are demanding high-quality food, which poses greater challenges for agricultural supply chains. The vast majority of supply chain research in the agri-food sector focuses on minimizing the last mile, with an emphasis on optimizing logistics costs and meeting demand. However, the first mile in the agricultural supply chain is also complex, as farmers need to organize an efficient harvesting process and efficient transport of harvested quantity to consolidation centers to ensure the delivery of high-quality products. This paper addresses this research gap by presenting a mixed-integer programming model based on the concepts of vehicle routing problems to optimize the logistic processes in the supply chain where the harvested products need to be picked up from different fields and transported to a depot. The aim is to minimize the total logistics costs incurred by visiting different fields during a pick-up round with multiple vehicles. The model has been applied to a case study in an agricultural cooperative in Greece as part of the European BBTWINS project focusing on agri-food value chain digitalization for resource efficiency. The main results show that the organization of the first mile in the agri-food supply chain using a cooled vehicle on a pick-up round minimizes logistics costs by up to 40% compared to the current situation.

Keywords: Supply chain managementvehicle routingmathematical optimizationfirst mile logistics