［Objective］To minimize passenger travel time while reducing operational costs for enterprises, it is necessary to identify an optimal balance between these two competing objectives. A systematic study on the stop plan for express/local trains on city rapid rail transit lines should be conducted based on both passenger travel costs and enterprise operational costs.［Method］Based on the characteristics of city rapid rail transit lines, a bi-objective nonlinear optimization model is developed, aiming to minimize passenger travel time and enterprise operational costs. According to genetic algorithm theory, a corresponding genetic algorithm program is constructed and the model is solved. Using an actual city rapid rail transit line as a study case, passenger flow OD (origin-destination) data during the morning peaks on a typical working day is used as the input. The optimal express/local train stop plan is obtained after line optimization using genetic algorithm. A comparative analysis is conducted on enterprise operational costs and passenger travel costs before and after the stop plan optimization.［Result & Conclusion］The stop plan verifies the effectiveness of the proposed model and algorithm. While the optimized stop plan for express/local trains on city rapid rail transit lines reduces passenger travel costs by 19.48%, increases enterprise operational costs by 4.23%, and leads to an overall cost reduction of 4.18%. Although the algorithm slightly increases operational costs for enterprises, it significantly reduces passenger travel time costs and improves overall passenger travel accessibility.