Route Optimization for Cold Chain Distribution with Mixed Fleets Considering Charging Station Alliance Strategy

With the strengthening of the country's carbon emission control efforts, cold chain logistics is facing the problem of reconfiguring fleets and optimizing routes to adapt to more stringent environmental standards while improving customer satisfaction. This study investigates the route optimization problem for cold chain logistics with mixed fleets and time windows, with a focus on exploring the application of mixed fleet and charging station alliance strategies in cold chain distribution. A three-objective optimization model is constructed to minimize total distribution cost, waiting time, and carbon emissions, and the IVY-NSGA-III hybrid algorithm is adopted for solving the model. The algorithm combines the efficient optimization ability of the Ivy algorithm and the global search ability of the NSGA-III algorithm, and an evaluation mechanism for solution quality is constructed. Based on the Solomon standard test instances, simulation instances are built to verify the effectiveness and feasibility of the algorithm. The results show that reasonable fleet ratios and charging station alliance strategies can effectively reduce enterprise distribution costs, improve customer satisfaction, and reduce carbon emissions. This study provides route optimization solutions for small and medium-sized cold chain logistics enterprises, thus possessing certain practical application value.