In order to solve the Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW)in the context of reverse logistics,the corresponding vehicle routing problem model was established according to the actual situation and solved by memetic algorithm. In the process of solving the model,the Guided Ejection Search (GES)was used to generate the initial population. In the process of population evolution,the Edge Assembly Crossover (EAX)method was used to generate the offspring,and in order to improve the quality of solutions and the search efficiency of algorithms,multiple neighborhood structures were used to repair and educate the offspring. The performance of memetic algorithm was tested and compared with Genetic Algorithm (GA),parallel-Simulate Annealing algorithm (p-SA) and Discrete Cuckoo Search(DCS)algorithm on Wang and Chen test dataset. Experimental results show that the proposed algorithm obtains the current optimal solutions when solving all small-scale examples;the algorithm updates or achieves current optimal solutions on 70% examples when solving the standard-scale examples,and the obtained optimal solution has more than 5% improvement compared with the current optimal solution,fully verifying the good performance of the algorithm for solving VRPSPDTW.