Volume 11, Issue 3 (9-2021)                   ASE 2021, 11(3): 3594-3613 | Back to browse issues page

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Salehpour M, Bagheri A. Pareto optimization of a nonlinear vehicle model using multi-objective differential evolution algorithm with fuzzy inference-based adaptive mutation factor (MODE-FM). ASE 2021; 11 (3) :3594-3613
URL: http://www.iust.ac.ir/ijae/article-1-595-en.html
Pareto optimization of a nonlinear vehicle model using multi-objective differential evolution algorithm with fuzzy inference-based adaptive mutation factor (MODE-FM)
Mohammad Salehpour , Ahmad Bagheri
Department of Mechanical Engineering, Bandar Anzali Branch, Islamic Azad University, Bandar Anzali, Iran
Abstract:   (6674 Views)
In this study, a multi-objective differential evolution with fuzzy inference-based dynamic adaptable mutation factor with hybrid usage of non-dominated sorting and crowding distance (MODE-FM) is utilized for Pareto optimization of a 5-degree of freedom nonlinear vehicle vibration model considering the five conflicting functions simultaneously, under different road inputs. The significant conflicting objective functions that have been observed here 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. Different road inputs are, namely, double-bump, stationary random road and non-stationary random road. It is exhibited that the optimum solutions of 5-objective optimization contain those of 2-objective optimization and, as a result, this important matter creates more options for optimal design of nonlinear vehicle vibration model.
Keywords: Nonlinear vehicle vibration model Pareto Differential evolution Multi-objective optimization Road input
Full-Text [PDF 3530 kb]   (5066 Downloads)    
Type of Study: Research | Subject: Vibration, noise, Acoustic
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