Low-Carbon Distribution Cuts Costs for Fresh Produce

Juping Shao, Fan Gao, and Yanan Sun developed an optimization model for delivering fresh agricultural products using multi-temperature vehicles under 3D loading constraints. The researchers addressed challenges in coordinating vehicle routes, maximizing space, and minimizing carbon emissions. They proposed a hybrid algorithm combining genetic algorithm and tabu search to efficiently solve the complex logistics problem.

The team validated their approach with data from a real-world agricultural supply chain. Their results indicate a joint distribution system reduces both total operating costs and carbon emissions.

This research demonstrates the benefits of integrating three-dimensional loading, multi-temperature distribution, and low-carbon goals. The model offers a practical tool for planning and decision-making in cold-chain logistics, potentially improving efficiency and sustainability in the fresh food sector.