Young Researchers and Elite Club, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
This paper presents a vibration damping optimization (VDO) algorithm to solve multi-objective optimization problems for the first time. To do that, fast non-dominated sorting and crowding distance concepts were used in order to find and manage the Pareto-optimal solution. The proposed VDO is validated using several examples taken from the literature. The results were compared with the multi-objective simulated annealing (MOSA) and non-dominated sorting genetic algorithms (NSGA-II) presented as the state-of-the-art in evolutionary multi-objective optimization algorithms. The results indicate that multi-objective VDO (MOVDO) shows better performances with significant difference in terms of computational timewhile NSGA-IIis better to find Pareto solutions. In other standard metrics, MOVDO is able to generate true and well-distributed Pareto optimal solutions and compete with NSGA-II and MOSA.