Research on Convergence Analysis of Multi Objective Optimization Algorithm for Lightweight Bus Chassis Architecture

The multi-objective optimization algorithm framework for lightweight bus chassis architecture selects new sample points by utilizing the optimal solution obtained during the iterative process, and then reshapes the dynamic Kriging surrogate model, ultimately achieving the implementation of multi-objective optimization for lightweight bus chassis architecture. Its core lies in whether the NM-MOPSO algorithm can accurately converge to the global optimal solution of the model. This determines the accuracy of the sampling area and the effectiveness of the new sample points. If the algorithm converges inaccurately, it will result in poor performance of the model in the optimal solution region, thereby affecting the accuracy of the solution. Therefore, the precise convergence of NM-MOPSO algorithm is crucial for the success of multi-objective optimization algorithm for lightweight bus chassis architecture.