Global Optimization using Particle Swarm Optimization and a Comparison with Evolutionary Algorithms and an Artificial Immune System

摘要

The paper is devoted to an application of the particle swarm algorithm to the optimization problems. The optimization of the known mathematical test functions (Rastrigin, Griewank, Branin and Goldstein-Price) is considered. On the base of the optimization of the test functions optimal parameters of the particle swarm optimizer are found. The comparisons of the particle swarm optimiser, an artificial immune system and evolutionary methods for the mathematical functions are presented. A few numerical examples for the swarm optimization of engineering optimization problems are also presented.