Multi-objective optimization of cable force of arch bridge constructed by cable-stayed cantilever cast-in-situ method based on improved NSGA-II

Abstract

The existing initial cable forces optimization method for arch bridges constructed by cable-stayed cantilever cast-in-situ method is computationally inefficient, and the single optimization objective cannot comprehensively consider the whole process of force state during the construction and operating periods of the arch ring. To solve the problems, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is improved in this study in terms of crowding, variation rate, elite individual preservation rate, and selection operator. A method of optimizing the initial cable force of the arch bridge constructed by cable-stayed cantilever cast-in-situ method based on the improved NSGA-II is proposed. A multi-objective optimization model of initial cable forces is constructed with the maximum tensile stress of the arch ring cross-section during the construction period and the eccentricity of the arch ring cross-section under dead load during the operating period as the optimization objectives. Combined with ANSYS and MATLAB, the optimization program based on the improved NSGA-II is implemented, and the optimization analysis of the initial cable forces is carried out with the Shuiluo River Bridge as an engineering example. The results show that the improved NSGA-II has better convergence and homogeneity than NSGA-II. The optimized initial cable forces based on the improved NSGA-II can simultaneously meet the control objectives during construction and operating periods. The optimization method proposed in this study has a very good global search capability, and can efficiently solve the optimization problem of the initial cable forces of the high-dimensional multi-objective of the arch bridge constructed by the cable-stayed cantilever cast-in-situ method.