Abstract
Cold chain logistics for perishable goods faces increasing challenges in balancing product quality and cost efficiency. This study proposes a mixed integer linear programming (MILP) model that jointly optimizes transportation and inventory decisions in temperature-controlled supply chains by incorporating both transportation and perishability-related holding costs within a multi-node distribution network. A real-world case study based on a ten-node cold chain system in Thailand is used to validate the model. The results indicate that the proposed approach effectively determines routing structures, shipment quantities, and vehicle utilization while accounting for product deterioration. Compared with experience-based planning, the proposed model reduces total logistics cost by 8.02%, primarily through improved transportation efficiency. These findings demonstrate the importance of integrating routing decisions with perishability considerations and highlight the model’s potential as a practical decision-support tool for cold chain logistics operations.