Sustainable Cold-Chain Vehicle Selection: A Novel AYBI-MUNRA MCDM Model

The part of the food supply chain that uses the most resources for transportation is the cold supply chain. For this reason, vehicle selection in the cold supply chain is a crucial task. Because there are several alternative vehicles and different criteria, choosing a vehicle is a challenging issue for decision makers. Six distinct cold-chain vehicle options were assessed with twelve sustainability (economic, environmental, and technological) criteria using an integrated Multi-Criteria Decision Making (MCDM) model. The main contribution and novelty of this study include developing a new Accordance-Yielding-Based Integration (AYBI) method for determining criteria weights. For vehicle evaluation and selection, the Multiple Normalization Rating Analysis (MUNRA) technique is applied. According to the AYBI, it was determined that Purchase Price (PP) is the most crucial criterion, followed by Infrastructure and Service Accessibility (ISA) and Load Capacity (LC), and Noise Emissions (NE) is the least significant criterion. According to the MUNRA results, the Twin-Axle Refrigerated Trailer (TRT) performs the best, followed by the Frigorific Trailer (Standard) (FT) and Double-Axle Refrigerated Truck (DART). The results also show that the developed AYBI method provides some advantages in the procedure of determining criteria weights. A sensitivity study verified the AYBI-MUNRA approach’s stability under various weight situations, and comparative analysis demonstrated its resilience in comparison to other MCDM methodologies.