An advanced particle swarm optimization algorithm and its application to search flutter critical velocity of bridges

Flutter may lead to collapse of long-span bridges and need to be avoided, which makes the estimation of the onset flutter essential for long-span bridge design. However, the efficiency of traditional solution methods of predicting onset flutter is not high. In this study, it is converted into an optimization model, which is solved by a proposed advanced particle swarm optimization (APSO) with a novel inertia weight strategy and mutation mechanism. Two well-known benchmark functions are firstly employed to validate the performance of APSO. Compared with other existing PSO methods, APSO not only has high accuracy, but also has the fastest convergence speed. Then, APSO is used to find the flutter critical wind speed of bridges. A good agreement is obtained comparing predictions on the onset flutter by the proposed methods and available tests on several study cases. In addition, the value range of APSO variables is discussed in depth. It is confirmed that the proposed APSO algorithm has excellent stability, robustness and fast convergence, which is suitable for searching onset flutter of bridges.