To solve simultaneous pickup and delivery among multiple demand points， a vehicle routing model that incorporates demand splitting and transfer is established. The constraint of dynamic variation of vehicle load， the constraint of multiple node access and the constraint of demand split transport are added in the model to improve the universality of the problem. In the optimization algorithm of the model， a hybrid approach combining arithmetic and ant colony optimization algorithm is employed to solve the problem. The algorithm follows a nested optimization structure， where the outer arithmetic optimization algorithm gets the task quantity of the delivery vehicle. The inner ant colony algorithm then optimizes the path， and provides feedback to the outer algorithm to continue to update and solve until the termination condition is met. At the same time， several enhancements are introduced to the hybrid arithmetic ant colony algorithm， such as incorporating probability coefficient， adding operator position update formula and updating dynamic tabu matrix. These enhancements aim to increase the diversity of solutions and improve the efficiency of the algorithm. Finally， the improved algorithm is verified by an example and compared with the hybrid whale algorithm and other algorithms to solve the problem in this paper.