Vehicle Routing in Precooling Logistics with Dynamic Temperature-Dependent Product Quality Decay

This study focuses on precooling operations for post-harvest fruits and vegetables in smallholder countries, aiming to provide an effective way to reduce product losses in the early stage of food supply chains. In this study, we consider the traditional centralized precooling and emerging mobile precooling to fulfill a series of small-scale and scattered precooling requests, with the goal of minimizing the total operating cost while guaranteeing the product quality of farmers. The resulting problem is a variant of the classic heterogeneous fleet vehicle routing problems with time windows, with the additional consideration of heterogeneous service and temperature-dependent product quality decay. The vehicle routing model is formulated by integrating product quality as a constraint in which a dedicated function is developed to capture the quality dynamics under changing temperatures. We design an improved adaptive large neighborhood search method to solve this problem by identifying a strategy that is able to deal with the interactions among decisions. Experiment results quantify the advantages of managing product quality in the early stage of supply chains for perishable products and provide management insights on conducting quality-based precooling services. Numerical experiments based on small-scale instances of the studied problem as well as large-scale benchmark instances verify the effectiveness and efficiency of the proposed algorithm by comparing it with CPLEX and three state-of-the-art algorithms.