Title :
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
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;
Conference_Titel :
Computational Intelligence and Security, 2008. CIS '08. International Conference on
Conference_Location :
Suzhou
Print_ISBN :
978-0-7695-3508-1
DOI :
10.1109/CIS.2008.43
