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

Author

Li, Xiang ; Li, Yanli ; Zhu, Li

Author_Institution

China Univ. of Geosci., Wuhan, China

Volume

2

fYear

2008

fDate

13-17 Dec. 2008

Firstpage

201

Lastpage

205

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 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.

Keywords

genetic algorithms; particle swarm optimisation; PSO; equilibrium; evolutionary algorithm; genetic algorithm; intelligence-optimizing method; optimizing multi-resources; particle swarm optimization; scheduling resources; Computational intelligence; Convergence; Design optimization; Evolutionary computation; Genetic algorithms; Geology; Job shop scheduling; Optimization methods; Particle swarm optimization; Security; Genetic algorithm; Particle swarm optimization; resources equilibrium;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Security, 2008. CIS '08. International Conference on

Conference_Location

Suzhou

Print_ISBN

978-0-7695-3508-1

Type

conf

DOI

10.1109/CIS.2008.43

Filename

4724765