Abstract: Purpose/Significance Multi-trip distribution allows vehicles to complete the distribution tasks between the distribution center and customer points. It has the advantages of low dispatch vehicle cost and high distribution efficiency. In the distribution, the customer’s demand cannot be determined due to the temporary lack of information, but it’s known that its approximate range shows grey uncertainty, which has an impact on the distribution decision. Design/Methodology Given the small sample and limited information of customers’ historical demand, the Grey-Markov model is constructed to predict the customers’ grey demand, and the multi-journey vehicle path optimization model with grey demand is then established. Due to the uncertainty of grey demand, the original distribution scheme needs to be optimized, and a multi-trip vehicle routing optimization strategy with real-time adjustment is proposed. Findings/Conclusions Aiming at the grey optimization model, an opportunity constraint method is introduced to design a model optimization solution algorithm based on grey simulation and tabu search algorithm. Finally, an example verifies that the optimization model and solution algorithm are feasible and effective.