AbstractDiaphragm wall structure retaining excavation of subway stations in soft soil generally involves large investments and considerable construction risks. A reasonable design is expected to provide a green life cycle solution for such structures. In this paper, the design of the existing enclosure structure of Hangzhou Metro Wenxin Station, China is examined. The analysis shows that the safety redundancy of the structure is high, but the economic performance is poor. This result is due to a lack of quantitative analysis of the degree of influence of uncertain parameters such as geotechnical parameters, construction variables, and loading parameters on the overall function of the system in design. To reduce construction risks and save materials, a multiobjective robustness design method based on correlation analysis is proposed in this study. The method is then applied to the design of a diaphragm wall retaining structure that considers safety, robustness, and economic cost, providing a reliable method for the application of smart and green life cycles in underground engineering. Because the empirical coefficient of variation (COV) of live loading parameters has significant influence on the overall performance of the system, a method based on correlation analysis is proposed to obtain an accurate COV that conforms to the actual situation and design parameters. First, considering the influence of geotechnical parameters and construction variations and the failure probability constraints of each failure mode, all feasible designs are obtained by the Monte Carlo method through comparative analysis. The Pareto frontier multiobjective optimization algorithm is introduced to find the node that reveals the balance between robustness and cost. Second, based on the obtained initial value nodes, the gray correlation degree is used to find the COV of the live loading parameter with the highest correlation degree of failure probability, and the corresponding COV is used as the calibration value to reobtain the new node with geotechnical parameters. When the COV of the live loading parameter obtained before and after the cycle is the same as that of the joint, a design parameter corresponding to the joint is the optimal design parameter, and the COV of the live loading parameter is the upper limit fluctuation threshold that the project should meet.