Hybrid Fleet Vehicle Routing Optimization and Multi-Case CO2 Emission Analysis

To reduce CO2 emissions from the transportation process, logistics companies are beginning to purchase electric vehicles (EVs) to replace fuel vehicles (FVs). To fully leverage the advantages of various vehicles, this study introduces three models: the vehicle energy consumption model, the power battery degradation model, and the Green Hybrid Vehicle Routing Problem (G-HVRP) model, which is constructed to minimize CO2 emissions. Finally, an improved Adaptive Large Neighborhood Search (ALNS) algorithm is designed to solve the established model. Using arithmetic examples, the connection between the ratio of a hybrid fleet and CO2 emissions in the distribution process was examined, and sensitivity analyses were carried out for variables such as speed, total vehicle mass, and number of customer points. The study revealed that, in regions with few thermal power plants, the CO2 reduction benefits of EVs were more pronounced. EVs emit the same CO2 as FVs at a specific speed and mass. Below this value, CO2 emissions are lower than those of FVs; above this value, they are greater. Recycling power batteries increases CO2 reductions for EVs. The results indicate that rationalizing vehicle choices according to actual circumstances is a necessary step in reducing CO2 emissions. Overall, the study shows that the sustainability of urban freight transport depends jointly on fleet composition, operating conditions, and the carbon intensity of the electricity used for charging, and it provides a quantitative basis for planning low-carbon, sustainable distribution fleets.