Parallel NSGA-III Based Multi-objective Optimization for Side Wall Section Size of High-speed Train Car-body

doi:10.3901/JME.2024.06.321

Abstract

Abstract: For many-objective optimization problems, traditional multi-objective optimization methods are limited due to insufficient diversity, slow convergence and computational cost in co-simulation, which are all critical issues that need to be taken into account in practical engineering. This study presents a SPMD parallel-based NSGA-III co-simulation optimization method, for which the framework is constructed by MATLAB optimizer and FEM solver, respectively. To improve the efficiency for high-dimensional optimization problems, multiple solvers are employed to calculate the fitness function in parallel optimization. Analysis on a simple profile example shows that, the parallel optimization presented in this study improves approximately twice as efficiency as that of the traditional serial approach under the rational utilization of computing resources. Taking the side wall of a high-speed train car-body as an objective, high-dimensional optimization under multi-conditions is implemented to analyze the sensitivity of structural strength and stiffness to the profiles’ thickness in different areas. Considering the Pareto solution set, the total mass of the side wall is reduced by 0.96%, while the bending and torsional stiffness are increased by 7.51% and 5.39% respectively, and the maximum stress is reduced by 12.18%. Compared with NSGA-II, NSGA-III can provide more solution sets that can meet the expectations for the optimization design of vehicle car-body structure.

Key words: NSGA-III algorithm, SPMD parallel, multi-objective optimization, co-simulation, high-speed train car-body

CLC Number:

U270

CHAI Yiyang, ZHANG Lele, DOU Weiyuan, ZHANG Haifeng. Parallel NSGA-III Based Multi-objective Optimization for Side Wall Section Size of High-speed Train Car-body[J]. Journal of Mechanical Engineering, 2024, 60(6): 321-333.

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