Improving genetic algorithms' performance by local search for continuous function optimization
CK Hamzaçebi
article (Uluslararası, Hakemli) | Yazar(lar): CK Hamzaçebi | Yıl: 2008 | Dergi/Kurum: APPLIED MATHEMATICS AND COMPUTATION | İndeks: WOS.SCI | DOI: 10.1016/j.amc.2007.05.068 | Anahtar Kelimeler: genetic algorithms, local search, random search, function minimization — Özet: The genetic algorithms (GAs) can be used as a g
The genetic algorithms (GAs) can be used as a global optimization tool for continuous and discrete functions problems. However, a simple GA may suffer from slow convergence, and instability of results. GAs' problem solution power can be increased by local searching. In this study a new local random search algorithm based on GAs is suggested in order to reach a quick and closer result to the optimum solution. (c) 2007 Elsevier Inc. All rights reserved.