MULTI-OBJECTIVE OPTIMIZATION OF WIND SCREEN HEIGHT FOR HIGH-SPEED RAILWAY BRIDGES BASED ON NSGA-II AND DEA HYBRID ALGORITHM

In order to explore the multi-objective optimization of wind screen height for high-speed railway bridges, the aerodynamic coefficients of the train and the bridge with different wind screen heights were analyzed, based on the theory of computational fluid dynamics. The roll stability moment coefficient of train and the drag coefficient of bridge were defined as optimization objectives. The height of wind screen was selected as design variable, and the multi-objective optimization genetic algorithm (NSGA-II) was employed as the optimization method to achieve the Pareto solution set. The optimal height of wind screen was obtained by using the Data Envelopment Analysis (DEA) to evaluate the relative efficiency of the Pareto solution set. The results show that it is feasible to add the NSGA-II and DEA hybrid algorithm to the multi-objective optimization of wind screen height for high-speed railway bridges. This optimization design method provides a new design method with the optimization problem of wind screen heights．