The Comparative Research of Solving Multi-task Scheduling Problems with GA and PSO

Abstract

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 Multi-task scheduling problem, discussed in detail the method of utilizing GA and PSO to equilibrium and optimize Multi-task scheduling problem under the constraints of resources separately. Through the analysis of comparative experiment, two kinds of intelligence-optimizing methods made very good results when solved a same problem, but in most cases, PSO had a faster rate of convergence than GA, but GA had a better convergent result than PSO.