In order to solve the problems of Automated Guided Vehicle （AGV） scheduling and conflict-free path planning in automated container terminals， an AGV conflict and congestion resolution strategy was proposed to generate conflict-free paths. Firstly， considering the capacity of the buffer bracket in the container yard as well as the constraints of no congestion on the operation paths and no conflict on the nodes， a two-stage mixed integer programming model was established based on the goal of the smallest maximum completion time and the shortest AGV transportation time. Then， an improved adaptive genetic algorithm and Dijkstra algorithm based on conflict and congestion resolution strategy were designed to obtain the AGV scheduling scheme and conflict-free paths. The results of numerical examples show that the improved adaptive genetic algorithm has the average solution time reduced by 13.56%， and the average gap rate of the objective function reduced by 9.01% compared to the genetic algorithm. Compared with the parking to wait strategy， the conflict and congestion resolution strategy has the congestion rate of the horizontal transportation area reduced by 67.6%， and the AGV waiting time reduced by 66.7%. It can be seen that the proposed algorithm has higher solving quality and faster speed， at the same time， the effectiveness of the proposed strategy is verified.