An optimised vehicle routing model for minimising distribution costs in cold-chain logistics

As economies and technology evolve, cold-chain logistics has emerged as a critical component in enhancing life quality and ensuring food safety. However, challenges remain due to incomplete technology and uneven customer distribution. This study proposes a routing model that integrates external temperature fluctuations into the cost calculations for simultaneous delivery and pick-up in cold-chain logistics. The model focuses solely on external temperature and examines its impact on distribution costs by analysing transportation, cargo damage, and refrigeration costs. To address the complexities of vehicle routing for simultaneous delivery and pick-up under variable external temperatures, this study enhances ant colony optimisation and genetic algorithms. Experimental results, based on multiple iterations, demonstrate that the improved model achieves lower overall distribution costs compared to traditional models, particularly in reducing cargo loss during transport and at customer nodes. These findings offer cold-chain logistics enterprises a more efficient, cost-effective strategy to reduce losses and boost efficiency.