The Comparative Research of Solving Problems of Equilibrium and Optimizing Multi-Resources with GA and PSO

摘要

Genetic algorithm and particle swarm optimization both belong to the evolutionary algorithms; they have much in common, but also have some differences. The paper set out from optimizing many resources, discussed the method of utilizing GA and PSO in detail, in order to equilibrium and optimize the problem of scheduling resources which are limited separately. Through analysis of comparative experiment, two kinds of intelligence-optimizing methods made very good results when solved a same problem, but in most cases, PSO has a faster rate of convergence than GA.