Research on Cable Force Optimization for the Construction of Reinforced Concrete Arch Bridges Based on Improved Whale Optimization Algorithm and Support Vector Machine

To address the issue of cable force optimization during the cantilever casting stage of reinforced concrete arch bridge construction, this study proposes a cable force optimization method based on an Improved Whale Optimization Algorithm (IWOA) combined with a Support Vector Machine (SVM) model. First, the standard Whale Optimization Algorithm is enhanced through Tent chaotic mapping, a nonlinear iterative control parameter, adaptive weight factors, and adaptive threshold strategies. The improved algorithm is then used to optimize key parameters (C, g) in the SVM model, constructing a parameter-optimized cable force combination-structure response prediction model for the arch bridge. Next, with the average tensile stress of the arch ring’s top and bottom slabs during construction and the bending strain energy after bridge completion as target variables, a multi-objective optimization mathematical model for cable forces during the construction stage of reinforced concrete arch bridges based on IWOA-SVM was established. Finally, the feasibility of the method was validated using the Shatuo Bridge project as a case study. The results indicate that compared to the finite element optimization method, the IWOA-SVM cable force optimization method significantly improved computational efficiency while ensuring optimization effectiveness. After optimization, the peak tensile stress and vertical displacement of each arch segment were significantly reduced, leading to improved internal force distribution and alignment, thereby enhancing the overall structural safety and reliability of reinforced concrete arch bridges.