Name
Abstract | ||
|---|---|---|
In this study, we use a new metaheuristic optimization algorithm, called bat algorithm (BA), to solve constraint optimization tasks. BA is verified using several classical benchmark constraint problems. For further validation, BA is applied to three benchmark constraint engineering problems reported in the specialized literature. The performance of the bat algorithm is compared with various existing algorithms. The optimal solutions obtained by BA are found to be better than the best solutions provided by the existing methods. Finally, the unique search features used in BA are analyzed, and their implications for future research are discussed in detail. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s00521-012-1028-9 | Neural Computing and Applications |
Keywords | DocType | Volume |
Bat algorithm, Constraint optimization, Metaheuristic algorithm | Journal | 22 |
Issue | ISSN | Citations |
6 | 1433-3058 | 115 |
PageRank | References | Authors |
3.98 | 30 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amir Hossein Gandomi | 1 | 1836 | 110.25 |
| Xin-She Yang | 2 | 5433 | 241.09 |
| Amir Hossein Alavi | 3 | 1016 | 45.59 |
| Siamak Talatahari | 4 | 381 | 16.76 |