<p>Mobile Edge computing (MEC) can effectively improve the computing efficiency and storage capacity of edge networks, reduce delay and improve user experience. Moreover, unmanned aerial vehicle (UAV)-assisted mobile edge computing has the characteristics of strong flexibility and easy deployment, which can provide high-quality services for mobile users more efficiently. However, problems such as task allocation, UAV deployment and limited energy consumption of UAVs are the main challenges faced by current research. In recent years, researchers at home and abroad have carried out a lot of research and analysis on this. In order to facilitate the research of scholars, this paper summarizes and sorts out the literature in this field, and points out some directions that can be further studied and developed, and is committed to promoting the development of edge computing. Firstly, this paper introduces the models of UAVs assisted mobile edge computing, including the local execution model, MEC execution model, and UAV hovering model. Secondly, it focuses on the related research of UAVs assisted mobile edge computing based on intelligent optimization algorithms, and expounds the advantages and disadvantages of different types of intelligent optimization algorithms in mobile edge computing. The optimization efficiency of several commonly used intelligent algorithms is compared through specific examples. Finally, the future development trend of UAV-assisted mobile edge computing based on intelligent optimization algorithm is analyzed and prospected.</p>