Pareto optimization of a five-degree of freedom vehicle vibration model using a multi-objective uniform-diversity genetic algorithm (MUGA)

• Published in: Engineering applications of artificial intelligence Vol. 23; no. 4; pp. 543 - 551
• Main Authors: Nariman-Zadeh, N., Salehpour, M., Jamali, A., Haghgoo, E.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2010
• Subjects: Automotive components; Displacement; Genetic algorithm; Mathematical models; MUGA; Multi-objective optimization Diversity; Optimization; Pareto; Pareto optimization; Tires; Vehicle vibration model; Vehicles; Vibration; Pareto; Vehicle vibration model; Multi-objective optimization Diversity; Genetic algorithm; MUGA
• ISSN: 0952-1976; 1873-6769
• DOI: 10.1016/j.engappai.2009.08.008

In this paper, a new multi-objective uniform-diversity genetic algorithm (MUGA) with a diversity preserving mechanism called the ε-elimination algorithm is used for Pareto optimization of a five-degree of freedom vehicle vibration model considering the five conflicting functions simultaneously. The important conflicting objective functions that have been considered in this work are, namely, seat acceleration, forward tire velocity, rear tire velocity, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Further, different pairs of these objective functions have also been selected for 2-objective optimization processes. The comparison of the obtained results with those in the literature demonstrates the superiority of the results of this work. It is shown that the results of 5-objective optimization include those of 2-objective optimization and, therefore, provide more choices for optimal design of a vehicle vibration model.