Allocating computing tasks to appropriate edge computing resources to meet the computing needs of users and improve the quality of service for user task requests is a key problem in edge computing. This paper proposes an edge computing task scheduling method (AFETSA) based on artificial fish swarm search. For improving the global search ability of the heuristic task scheduling algorithm and reducing the computation time delay, the artificial fish search algorithm was combined with the edge computing task scheduling model, and the field of view and step size of the artificial fish were dynamically adjusted by the nonlinear decreasing function. At the same time, for improving the optimization ability of the algorithm, the tabu search algorithm is fused, and the tabu list is introduced to prevent the algorithm from falling into local optimal in each iteration. The experimental evaluation results on the CloudSim3. 0 simulation platform, show that compared with the existing task scheduling algorithms AFSA, ACO and PSO, the proposed task scheduling method in this paper has significant improvement in task execution time, algorithm stability and load balance. It can make full use of the computing resources of edge servers to improve the computing performance of computing tasks, and effectively solve the problem of high delay and load imbalance caused by uneven task scheduling in edge computing.