The work aims to explore the fresh commodity multi-compartment loading distribution routing optimization problem based on vehicle sharing to deal with the deficiencies of fresh commodities logistics distribution optimization research in the reasonable combination of vehicle sharing scheduling and multi-compartment loading distribution. First, a mathematical model to minimize the operating cost was established based on the temperature control conditions of fresh commodities and the loading constraints of the multi-compartment. Second, a hybrid ant colony-tabu search algorithm was designed to solve the model, and a selective assignment mechanism and a vehicle-sharing strategy were introduced to improve the optimization capability. Then, the effectiveness of the proposed model and algorithm was verified through comparative analysis with particle swarm optimization, large neighborhood search algorithm, and differential evolution algorithm. Finally, combined with examples, relevant indexes before and after optimization were compared and analyzed, a vehicle route optimization scheme was proposed, and a sensitivity analysis of compartment capacity was conducted. The optimized operating cost was reduced by 43.53%, the average loading rate was increased by 25%, and the reasonable segmentation of service period and selection of compartment capacity could effectively improve the average loading rate of vehicles and reduce the value loss of fresh commodities. The proposed model, algorithm, and vehicle-sharing strategy can reasonably schedule the distribution route and reduce the operating cost and value loss of fresh commodity, which provides methodological references and theoretical supports for the fresh commodities multi-compartment loading distribution routing optimization based on vehicle sharing.