کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
491128 | 719569 | 2016 | 8 صفحه PDF | دانلود رایگان |
This paper presents a constrained multi-objective optimization study of vehicle passive suspension system which is modeled as a passive half car ride model. For multi-objective optimization the most widely used multi-objective evolutionary algorithms such as NSGA-II, SPEA2 and PESA-II are employed. The potential of the MOEAs in obtaining the better Pareto front of optimal solutions and in maintaining the diversity among the optimal solutions is tested by conducting 2 and 3-objective optimization studies. The results show that NSGA-II is able to yield a better Pareto front in terms of minimizing the objective vector but SPEA2 and PESA-II has a better diversified set of optimal solutions. Overall, all three algorithms have performed equally in optimizing the problem with the nature of the equations is second order ordinary differential equations.
Journal: Procedia Technology - Volume 23, 2016, Pages 361-368