In order to solve the problem of uneven allocation of airspace resources in traditional artificial sectors based on subjective experience, and to meet the needs of today's air traffic operation, the problem of three-dimensional sectorization in terminal areas was studied by improving Agent method. Firstly, while adhering to traditional sectoring constraints, the objective was to enhance sector adaptability to traffic flows and achieve a reduction and balance in air traffic control workload. Subsequently, the traditional Agent method was improved by using genetic algorithm to determine the location of Agent initial solution, so that it could enhance computational efficiency, designing and optimizing Agent growth rules and spatial filling rules. Finally, using the Shanghai terminal area as a case study, the results indicated that the improved Agent method yields sector planning scheme with respective improvements of 25.84% and 18.54% in sector shape characteristics and adaptability to airborne traffic flows. Simultaneously, while reducing the overall terminal area air traffic control workload, the standard deviation of control workload among sectors was reduced by 53.33% and 36.58%, respectively, compared to the existing and traditional Agent methods. It can be seen that the Research on Improved Agent-Based Sectorization Method provides reference for the local characteristic airspace planning of our country.