Name
Abstract | ||
|---|---|---|
A recently developed metaheuristic optimization algorithm, firefly algorithm (FA), mimics the social behavior of fireflies based on the flashing and attraction characteristics of fireflies. In the present study, we will introduce chaos into FA so as to increase its global search mobility for robust global optimization. Detailed studies are carried out on benchmark problems with different chaotic maps. Here, 12 different chaotic maps are utilized to tune the attractive movement of the fireflies in the algorithm. The results show that some chaotic FAs can clearly outperform the standard FA. (c) 2012 Elsevier B.V. All rights reserved. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.cnsns.2012.06.009 | Communications in Nonlinear Science and Numerical Simulation |
Keywords | DocType | Volume |
Firefly algorithm,Chaos,Metaheuristic algorithm,Global optimization | Journal | 18 |
Issue | ISSN | Citations |
1 | 1007-5704 | 87 |
PageRank | References | Authors |
2.70 | 7 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir Hossein Gandomi | 1 | 1836 | 110.25 |
| Xin-She Yang | 2 | 5433 | 241.09 |
| Siamak Talatahari | 3 | 381 | 16.76 |
| Amir Hossein Alavi | 4 | 1016 | 45.59 |