A fast annealing evolutionary algorithm for global optimization
By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing techni...
| Publié dans: | Journal of computational chemistry. - 1984. - 23(2002), 4 vom: 22. März, Seite 427-35 |
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| Format: | Article |
| Langue: | English |
| Publié: |
2002
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| Accès à la collection: | Journal of computational chemistry |
| Sujets: | Journal Article |
| Résumé: | By combining the aspect of population in genetic algorithms (GAs) and the simulated annealing algorithm (SAA), a novel algorithm, called fast annealing evolutionary algorithm (FAEA), is proposed. The algorithm is similar to the annealing evolutionary algorithm (AEA), and a very fast annealing technique is adopted for the annealing procedure. By an application of the algorithm to the optimization of test functions and a comparison of the algorithm with other stochastic optimization methods, it is shown that the algorithm is a highly efficient optimization method. It was also applied in optimization of Lennard-Jones clusters and compared with other methods in this study. The results indicate that the algorithm is a good tool for the energy minimization problem |
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| Description: | Date Completed 24.10.2002 Date Revised 03.11.2003 published: Print Citation Status PubMed-not-MEDLINE |
| ISSN: | 1096-987X |