基于智能算法的斜拉桥成桥索力优化研究

Research on Cable Force Optimization of Cable-Stayed Bridge at Completion Based on Intelligent Algorithms

摘要: 以实际公铁两用斜拉桥为研究对象，建立全桥有限元模型。基于影响矩阵法，计算各斜拉索索力调整对桥梁关键单元节点位移的定量影响程度。建立2种控制结构变形的目标函数，选取遗传算法、粒子群优化算法和模拟退火算法3种智能优化算法作为寻优工具，对比不同组合的索力优化结果。结果表明：主梁线形优化中，粒子群算法对最优解的逼近程度以及迭代收敛时间优于遗传算法和模拟退火算法；仅以主梁平顺为目标函数时，虽然主梁线形得到改善，但会导致桥塔产生较为显著的变形；采用“塔直梁平”作为目标函数，兼顾了主梁线形优化，同时桥塔变形得到大幅改善，索力优化结果更符合实际工程对斜拉桥成桥线的要求。

Abstract: Taking an actual road-rail cable-stayed bridge as the research object, a finite element model was established. Based on the influence matrix method, the quantitative impact of the adjustment of each cable force on the displacement of key unit nodes of the bridge was calculated. Two types of objective functions for controlling structural deformation were established, and three intelligent optimization algorithms, namely genetic algorithm, particle swarm optimization algorithm, and simulated annealing algorithm, were selected as optimization tools to compare the optimization results of different combinations of cable forces. The results show that in the optimization of the main beam profile, the particle swarm optimization algorithm has better approximation to the optimal solution and faster iterative convergence time than the genetic algorithm and simulated annealing algorithm. When only the smoothness of the main beam is used as the objective function, although the profile of the main beam is improved, it will cause significant deformation of the bridge tower. Using “straight tower and flat beam” as the objective function not only optimizes the profile of the main beam but also significantly improves the deformation of the bridge tower, and the cable force optimization results are more in line with the requirements of the actual engineering for the final profile of the cable-stayed bridge.