The multi-trip vehicle routing problem with simultaneous deliveries and pickups (MTVRPSDP) was studied in consideration of the loading and discharging time,maximum vehicle transport time and load capacity.A linear integer programming model for the MTVRPSDP was formulated,in which the objective function was to minimize the total distribution costs including vehicle costs and transportation costs.A quantum-inspired ant colony optimization (QACO) algorithm for solving the MTVRPSDP was proposed by combining the quantum computing and basic ant colony optimization (ACO).Owing that the transition probability of artificial ants was improved by using the heuristic factor of quantum bits in the QACO,the global search ability and stability of the algorithm have a better improvement,and its disadvantage of getting into the local optimum is also effectively weakened.The numerical results show that the linear integer programming model for the MTVRPSDP is feasible and effective in real application.The solutions obtained by using the basic ACO,QACO and other state-of-art algorithms presented in literatures were compared,and the conclusion shows that the distribution routes,obtained by using the QACO to solve the linear integer programming model for MTVRPSDP,are better in terms of economic efficiency and reasonability.