To address the issue of subjective uncertainty in the formulation and implementation of maintenance and strengthening strategies for existing bridges, this study proposed a bridge operation and maintenance decision-making framework that incorporates reinforcement time intervals. Firstly, based on the concept of interval mathematics, interval numbers were introduced to quantify subjective uncertainties that cannot be described using probability theory. Secondly, by leveraging the high efficiency and accuracy of surrogate models, the framework enables the direct mapping of the worst-case reliability index under mixed probabilistic and interval uncertainties. Finally, the multi-objective optimization algorithm NSGA-‍ Ⅱ was employed to efficiently drive the framework, ensuring optimized decision-making outcomes. To verify the applicability of the proposed framework in practical engineering scenarios, a typical prefabricated simply supported T-beam bridge was selected as a case study. Based on field data obtained from a Weigh-In-Motion (WIM) system, a probabilistic model of vehicle load effects was established. A time-dependent resistance degradation model was then introduced to optimize the operation and maintenance strategy for the T-beam bridge, culminating in the development of a decision-making library for its maintenance and reinforcement. The results indicate that strategies with smaller time intervals correspond to smaller Life Cycle Cost (LCC) and lower permissible subjective uncertainty. Conversely, strategies with longer time intervals, while resulting in higher LCC, offer greater flexibility for construction and decision-making processes. For simply supported T-beam bridges with spans ranging from 20 to 40 meters, it is possible to meet the required reliability index over the service life while minimizing LCC through appropriate reinforcement strategies. These findings demonstrate the strong applicability of the proposed framework and suggest it can serve as a methodological foundation for formulating maintenance and reinforcement strategies for existing bridges.