This study addresses the stability problem of long-span cable-supported bridges (CSBs) under live loads, which requires an accurate estimation of maximum girder deflection and rotation angle. In contrast to the cumbersome influence line method or analytical method, which ignores the structural nonlinearity of this bridge type or uses too many constraint conditions, we convert this problem into an optimization task. Since the number of segments of distributed live loads under which maximum girder deflection and rotation angle occur (i.e., the number of optimization variables) is unknown due to CSB’s structural complexity, a multi-population competition genetic algorithm (MPCGA), inspired by the population competition theory in ecology, is applied. It incorporates the Lotka-Volterra competition model to depict the changing sizes of the competing populations. We designed the interspecies migration and exchange mechanism for the above engineering problem and ran ANSYS to compute individual fitness. This algorithm offers high accuracy and efficiency in solving the maximum girder deflection and rotation angle of the long-span CSB, the positions where the maximum girder deflection and rotation angle occur, and the corresponding live load patterns. Finally, the proposed method is validated by a case study of a hybrid CSB with a main span of 1400 m. The calculation results obtained via the conventional influence line and proposed methods are compared, proving the latter’s supremacy.

中文翻译：

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用于评估大跨度索支承桥梁在活荷载下最大挠度和旋转角度的多群体竞争遗传算法：一种直接优化任务解决方案


该文解决了大跨度索支撑桥 （CSB） 在活荷载作用下的稳定性问题，需要准确估计最大梁挠度和旋转角度。与忽略这种桥梁类型的结构非线性或使用过多约束条件的繁琐影响线方法或解析方法相反，我们将这个问题转化为优化任务。由于 CSB 的结构复杂性，发生最大梁挠度和旋转角度的分布式活荷载的段数（即优化变量的数量）是未知的，因此应用了受生态学种群竞争理论启发的多种群竞争遗传算法 （MPCGA）。它结合了 Lotka-Volterra 竞争模型来描述竞争种群规模的变化。我们为上述工程问题设计了种间迁移和交换机制，并运行 ANSYS 来计算个体适应度。该算法在求解大跨度 CSB 的最大梁挠度和旋转角度、最大梁挠度和旋转角度发生的位置以及相应的活荷载模式方面具有很高的准确性和效率。最后，通过主跨度为 1400 m 的混合 CSB 实例分析验证了所提方法的有效性。将常规影响线得到的计算结果与所提出的方法进行了比较，证明了后者的优越性。