Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor

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SALEHPOUR M.; JAMALI A.; BAGHERI A.; NARIMAN ZADEH N.

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Journal Paper

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Journal: Automotive Science and Engineering Year:2018 | Volume:8 | Issue:4 Page(s): 2854-2867

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Title

Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor

Author(s)

SALEHPOUR M. | JAMALI A. | BAGHERI A. | NARIMAN ZADEH N. | Issue Writer Certificate

Keywords

Five degree of freedom vehicle vibration model

Non-stationary random road

Pareto

Multi-objective optimization

Differential evolution Fuzzified mutation

Abstract

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 biobjective 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.

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APA: Copy

SALEHPOUR, M., JAMALI, A., BAGHERI, A., & NARIMAN ZADEH, N.. (2018). Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor. AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING), 8(4), 2854-2867. SID. https://sid.ir/paper/321833/en

Vancouver: Copy

SALEHPOUR M., JAMALI A., BAGHERI A., 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. AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING)[Internet]. 2018;8(4):2854-2867. Available from: https://sid.ir/paper/321833/en

IEEE: Copy

M. SALEHPOUR, A. JAMALI, A. BAGHERI, and N. NARIMAN ZADEH, “Optimum Pareto design of vehicle vibration model excited by non-stationary random road using multi-objective differential evolution algorithm with dynamically adaptable mutation factor,” AUTOMOTIVE SCIENCE AND ENGINEERING (INTERNATIONAL JOURNAL OF AUTOMOTIVE ENGINEERING), vol. 8, no. 4, pp. 2854–2867, 2018, [Online]. Available: https://sid.ir/paper/321833/en

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