High dimensional multi-objective optimization of car door
In order to improve the mechanical properties of an MPV door and reduce the quality of the door assembly,aiming at the problem that the traditional optimization algorithm is prone to poor solution convergence of high-dimensional multi-objective optimization,NSGA-Ⅲ algorithm based on non-dominated ranking and reference points was used to optimize the door multi-objective by combining experimental design and response surface model.The results showed that the error between the simulation results and the experimental values of each target of the initial door model were less than 5%,and the consistency was good.The constructed response surface had high accuracy;The Pareto solutions obtained by NSGA-Ⅲ algorithm had uniform distribution and good convergence.After optimization,the first order frequency of the door and the stiffness of the door framed was not significantly improved,but still met the requirements of the enterprise.The weight of the door was reduced by 13.63%,and the lightweight effect were obvious.It showed that the application of NSGA-Ⅲ algorithm can effectively solve the problem of poor convergence of traditional optimization high-dimensional objectives,and obtain relatively ideal results.
car doormulti-objective optimizationnon-dominated sorting genetic algorithmlightweighthammersley
NETL
NSTL
万方数据
