New hybrid approach HNSGA-III&SPEA/R: Application to optimization of powertrain mount system stiffness parameters

Abstract

In this study, a new methodology, hybrid NSGA-III with SPEA/R (HNSGA-III&SPEA/R), has been developed to design and achieve cost optimization of powertrain mount system stiffness parameters. This problem is formalized as a multi-objective optimization problem involving six optimization objectives: mean square acceleration and mean square displacement of the powertrain mount system. A hybrid HNSGA-III&SPEA/R is proposed with the integration of Strength Pareto evolutionary algorithm based on reference direction for Multi-objective (SPEA/R) and Many-objective optimization genetic algorithm (NSGA-III). Several benchmark functions are tested, and results reveal that the HNSGA-III&SPEA/R is more efficient than the typical SPEA/R, NSGA-III. Powertrain mount system stiffness parameters optimization with HNSGA-III&SPEA/R is simulated respectively. It proved the potential of the HNSGA-III&SPEA/R for powertrain mount system stiffness parameter optimization problem.