Hybrid Particle Swarm Optimizer with Mutation

摘要

This paper presents a Hybrid Particle Swarm Optimizers combining the idea of the particle swarm with concepts from Evolutionary Algorithms. The hybrid Particle Swarm Optimizers with Mutation (HPSOM) combine the traditional velocity and position update rules with the idea of numerical mutation. This model is tested and compared with the standard PSO on unimodal and multimodal functions. This is done to illustrate that PSOs with mutation operation have the potential to achieve faster convergence and the potential to find a better solution. The objective of this paper is to describe the HPSOM model and to test their potential and competetiveness on function optimization.