Modified Particle Swarm Optimization Algorithm for Multi Objective Optimization Design of Hybrid Journal Bearings

Abstract

The objective of design optimization is to determine the design that minimizes the objective function by changing design variables and satisfying design constraints. During multiobjective optimization, which has been widely applied to improve bearing designs, designers must consider several design criteria or objective functions simultaneously. The particle swarm optimization (PSO) method is known for its simple implementation and high efficiency in solving multifactor but singleobjective optimization problems. This paper introduces a new multiobjective algorithm (MOA) based on the PSO and Pareto methods that can greatly reduce the number of objective function calls when a suitable swarm size is set.