A novel Pareto-based multi-objective vibration damping optimization algorithm to solve multi-objective optimization problems

This paper presents a Vibration Damping Optimization (VDO) algorithm to solve multi-objective optimization problems for the first time. To do this, 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 Multi-Objective Simulated Annealing (MOSA) and Non-dominated Sorting Genetic Algorithms (NSGA-II) presented as state-of-the-art in evolutionary multi-objective optimization algorithms. The results indicate that Multi-Objective VDO (MOVDO) gives better performance with a significant difference in terms of computational time, while NSGA-II is better in finding 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. (C) 2014 Sharif University of Technology. All rights reserved.