Volume 8, Issue 4 (12-2018)                   ASE 2018, 8(4): 2854-2867 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Salehpour M, Jamali A, Bagheri A, N. Nariman-zadeh N. Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor. ASE 2018; 8 (4) :2854-2867
URL: http://www.iust.ac.ir/ijae/article-1-487-en.html
University of Guilan,Mechanical Engineering
Abstract:   (20008 Views)
In this paper, a new version of multi-objective differential evolution with dynamically adaptable mutation factor is used for Pareto optimization of a 5-degree of freedom vehicle vibration model excited by non-stationary random road profile. In this way, non-dominated sorting algorithm and crowding distance criterion have been combined to differential evolution with fuzzified mutation in order to achieve multi-objective meta-heuristic algorithm. To dynamically tune the mutation factor, two parameters, named, number of generation and population diversity are considered as inputs and, one parameter, named, the mutation factor as output of the fuzzy logic inference system. Conflicting objective functions that have been observed to be optimally designed simultaneously are, namely, vertical seat acceleration, vertical forward tire velocity, vertical rear tire velocity, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Furthermore, different pairs of these objective functions have also been chosen for bi-objective optimization processes. The comparison of the obtained results with those in the literature unveils the superiority of the results of this work. It is displayed that the results of 5-objective optimization subsume those of bi-objective optimization and, consequently, this achievement can offer more optimal choices to designers.
Full-Text [PDF 1503 kb]   (4003 Downloads)    
Type of Study: Research | Subject: Control

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2022 All Rights Reserved | Automotive Science and Engineering

Designed & Developed by : Yektaweb