Optimizing Dual Distribution Scheme in Pharmaceutical Cold Chain for Cost and Carbon Emissions Reduction

Abstract

The reduction in comprehensive costs and carbon emissions in the process of trans-regional and multi-seasonal pharmaceutical cold chain logistics is a highly debated topic. To simultaneously address these issues, we propose a dual distribution method based on the vehicle routing problem (VRP), wherein either a refrigerated truck or van equipped with a refrigerated container is selected for drug delivery. To verify the effectiveness of this method, we design a comparison function to calculate the depletion of consumables and create a better distribution scheme for customer nodes in multiple temperature zones with various demands. To further optimize the model, we introduce the Grey Wolf Optimizer (GWO) to establish a large-scale neighborhood search vehicle routing model. Additionally, we utilize the greedy algorithm and an upgraded nonlinear factor to accelerate convergence speed and enhance accuracy. Ultimately, our experiments demonstrate significant advantages over existing algorithms, while providing valuable insights into economical and environmentally friendly pharmaceutical cold chain logistics.

Keywords

• pharmaceutical cold chain
• improved grey wolf algorithm
• dual distribution scheme
• temperature difference
• refinement of consumables