A fast annealing evolutionary algorithm for global optimization

✍ Scribed by Wensheng Cai; Xueguang Shao

• Publisher: John Wiley and Sons
• Year: 2002
• Tongue: English
• Weight: 136 KB
• Volume: 23
• Category: Article
• ISSN: 0192-8651
• DOI: 10.1002/jcc.10029

✦ Synopsis

Abstract

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. © 2002 Wiley Periodicals, Inc. J Comput Chem 23: 427–435, 2002; DOI 10.1002/jcc.10029