| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 4634678 | Applied Mathematics and Computation | 2008 | 9 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Coşkun Hamzaçebi,