Research on Delivery Route Optimization for Electric Cold-Chain Logistics Vehicles Under Public–Private Charging Modes

Electric logistics vehicles have been increasingly applied in various delivery scenarios due to their environmental benefits. However, limitations in battery capacity and the availability of charging infrastructure remain major obstacles to their wider adoption. This study develops a route optimization model for electric cold-chain logistics vehicles with the objective of minimizing total costs. The model incorporates multiple constraints, including charging mode selection, maximum vehicle capacity, and customer time windows. Computational results show that different charging modes have distinct effects on the total delivery cost of electric cold-chain logistics vehicles. Compared with the public charging mode, the public–private charging mode can achieve lower delivery costs. Moreover, as the difference in unit charging costs between public and private charging stations increases, electric cold-chain logistics vehicles are more likely to utilize charging stations that are farther away but offer lower charging costs.