Optimizing routing paths in IoT Wireless Sensor Networks (WSNs) is crucial for efficient data transmission. The fault tolerance of data transmission is intricately linked to various uncertain variables, encompassing dynamic environmental conditions, equipment malfunctions, and intricate network topologies. Therefore, pre-constructing multiple optimized paths becomes essential to effectively manage uncertainties in real-time scenarios. Nonetheless, prevailing optimization techniques for multi-path routing in wireless sensor networks often neglect the consideration of sensor device reliability and the possible inconsistency between transmission reliability and energy consumption. Moreover, identifying all non-dominated paths for multi-objective optimization problems consumes excessive time. In this study, addressing the optimization objectives of both reliability and energy consumption, we introduce a Fast Bi-objective Multi-path Search (FBMS) algorithm tailored to swiftly generate multiple paths. These paths are strategically disjointed within the decision space to achieve a balanced distribution of transmission loads. The proposed method significantly reduces the time required to identify multiple non-dominated solution paths compared to conventional approaches. The experimental results validate the efficiency and effectiveness of the proposed algorithm.