Journal Article

Cable Force Optimization in Cable-Stayed Bridges Using Gaussian Process Regression and an Enhanced Whale Optimization Algorithm

Zhang, Pengtao, Cai, Shunyao, Tu, Bing, Jiao, Chongyuan

2025

Overview

Optimizing cable forces in cable-stayed bridges is challenging due to structural nonlinearity and the limitations of traditional methods, which often focus on isolated performance indicators. This study proposes an integrated framework combining Gaussian process regression (GPR) with an enhanced whale optimization algorithm improved by the Salp Swarm Algorithm (EWOSSA). GPR is first used to model the nonlinear relationship between cable forces and structural responses. The EWOSSA then efficiently optimizes the GPR-based model to identify optimal cable forces. A case study on a cable-stayed bridge with a 2 × 145 m main spans demonstrates the effectiveness of the proposed approach. Compared with conventional methods such as the internal-force equilibrium and zero-displacement methods, the EWOSSA-GPR framework achieves superior performance across multiple structural metrics. It ensures a more uniform cable force distribution, reduces girder displacements, and improves bending moment profiles, offering a comprehensive solution for optimal structural performance in cable-stayed bridges.

• Publisher: MDPI AG
• Subject: Accuracy / Algorithms / Artificial intelligence / Bending moments / Bridges / Business metrics / cable force optimization / Cable-stayed bridges / Case studies / Comparative analysis / Efficiency / enhanced whale optimization algorithm / Equilibrium / Finite element analysis / Force distribution / Gaussian process / Gaussian process regression / Gaussian processes / Highway construction / Integrated approach / Load / Machine learning / Marine mammals / Mathematical optimization / Mechanical properties / Methods / Nonlinear systems / Nonlinearity / Optimization / Optimization algorithms / Random variables / salp swarm algorithm / Structural response