Cable Force Optimization Analysis of Cable‐Stayed Bridges Based on the Plant Growth Simulation Algorithm

ABSTRACT

The overall structural performance of cable‐stayed bridges critically depends on the rational distribution of cable forces. Traditional analytical methods and mainstream intelligent optimization algorithms often suffer from limited global search capability, strong parameter sensitivity, or low computational efficiency under high‐dimensional, multi‐constraint, and nonlinear coupling conditions. To address these challenges, this study proposes a cable force optimization method based on the plant growth simulation algorithm (PGSA) and systematically evaluates the bridge's overall structural behavior through finite element analysis. The method employs plant tropism and branching mechanisms to construct a parameter‐free global search strategy, enabling escape from local optima and efficient convergence to the global optimum. A variable‐step parallel search mechanism is further introduced to balance global exploration and local refinement, while geometric nonlinearity and multiple construction‐stage scenarios are incorporated to achieve force–form coupled optimization. A multi‐objective, multi‐scenario optimization framework is established for both construction and in‐service states, and a closed‐loop coupling between PGSA and finite element analysis enhances the stability and robustness of high‐dimensional cable force optimization. Numerical examples on representative cable‐stayed bridges demonstrate that the optimized cable forces achieve more uniform distribution, effectively control bending moments and vertical displacements of the main girder, and improve the overall structural performance. The results indicate that the proposed approach overcomes the limitations of traditional intelligent algorithms regarding parameter sensitivity and local convergence, providing an efficient, robust, and generalizable strategy for cable force optimization in complex cable‐stayed bridges.