Application Research on Cable Force Optimization of Cable-Stayed Bridge Based on Improved Grey Wolf Algorithm

For complex structures, the solution process of existing cable force optimization methods for low-tower cable-stayed bridges is characterized by a significant number of matrix operations, which require substantial computing power and time. As a result, achieving a more accurate solution becomes exceedingly difficult. To tackle this challenge, we propose a new cable force optimization method that enhances the stress distribution of the cable-stayed cables in the completed state of the bridge. This approach minimizes the need for frequent adjustments to cable forces and alterations to the linear elevation of the beam bridge during construction. In this study, the low-tower cable-stayed bridge of the Lanjiang Bridge serves as the engineering background. By integrating finite element analysis with a multi-objective optimization method, we propose an optimization approach for the real-time correction of cable forces during the construction of long-span low-tower cable-stayed bridges. Within this optimization framework, the cable forces during construction are treated as variable parameters, while the linear elevation of the completed bridge is imposed as a constraint. The improved grey wolf algorithm is integrated with the finite element algorithm, and the key parameters of the support vector machine are optimized using this method, resulting in the optimal parameter combination predicted based on the training samples. The results indicate that after optimizing the support vector machine model using the improved grey wolf algorithm, the cable force distribution of the cable-stayed cables becomes more uniform, with a variance of 19.96. Additionally, the maximum displacement change of the main beam under the influence of the dead load is reduced by 33.48%. This method demonstrates high optimization efficiency and produces favorable outcomes, highlighting its value in calculating cable forces and guiding construction processes during the erection of cable-stayed cables for similar bridges.

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Publication Details

Journal
Buildings
Published
2025-04-16
DOI
https://doi.org/10.3390/buildings15081309
Citations
2
Primary Topic
Structural Engineering and Vibration Analysis
Type
article
Field-Weighted Citation Impact
1.91
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article

Application Research on Cable Force Optimization of Cable-Stayed Bridge Based on Improved Grey Wolf Algorithm

Hongzhe Guo, Yu‐Zhong Zhang, Li Zhu, Jian Guo
2 citations
Buildings
Structural Engineering and Vibration Analysis
1.91
article

Application Research on Cable Force Optimization of Cable-Stayed Bridge Based on Improved Grey Wolf Algorithm

Hongzhe Guo, Yu‐Zhong Zhang, Li Zhu, Jian Guo
article en
2 citations

Abstract

For complex structures, the solution process of existing cable force optimization methods for low-tower cable-stayed bridges is characterized by a significant number of matrix operations, which require substantial computing power and time. As a result, achieving a more accurate solution becomes exceedingly difficult. To tackle this challenge, we propose a new cable force optimization method that enhances the stress distribution of the cable-stayed cables in the completed state of the bridge. This approach minimizes the need for frequent adjustments to cable forces and alterations to the linear elevation of the beam bridge during construction. In this study, the low-tower cable-stayed bridge of the Lanjiang Bridge serves as the engineering background. By integrating finite element analysis with a multi-objective optimization method, we propose an optimization approach for the real-time correction of cable forces during the construction of long-span low-tower cable-stayed bridges. Within this optimization framework, the cable forces during construction are treated as variable parameters, while the linear elevation of the completed bridge is imposed as a constraint. The improved grey wolf algorithm is integrated with the finite element algorithm, and the key parameters of the support vector machine are optimized using this method, resulting in the optimal parameter combination predicted based on the training samples. The results indicate that after optimizing the support vector machine model using the improved grey wolf algorithm, the cable force distribution of the cable-stayed cables becomes more uniform, with a variance of 19.96. Additionally, the maximum displacement change of the main beam under the influence of the dead load is reduced by 33.48%. This method demonstrates high optimization efficiency and produces favorable outcomes, highlighting its value in calculating cable forces and guiding construction processes during the erection of cable-stayed cables for similar bridges.

BuildingsVol. 15(8)
Lanzhou Jiaotong University (CN), China Railway Group (China) (CN), Monash University (AU)
Openalex Percentile: Top 16%
Structural Engineering and Vibration Analysis
1.91
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