Name
Abstract | ||
|---|---|---|
In fruit fly optimization algorithm (FOA), the search speed of each fruit fly is fast, but when it traps into the local optimum, it is difficult to re-find a better solution. In order to overcome this drawback, we propose an improved version of FOA, termed as 3D-FOAdis. In the proposed method, three-dimensional coordinates and the disturbance mechanism were both introduced. We firstly extends the original two-dimensional coordinates to three-dimensional coordinates, where fruit flies can fly more widely so that it is more likely to jump out of the local optimum. Then we introduce a disturbance mechanism force the FOA to find better solutions when the fruit flies fall into the local optimums. The effectiveness of 3D-FOAdis has been rigorously evaluated against the nine benchmark functions. The experimental results demonstrate that the proposed approach outperforms the other two counterparts. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-61824-1_67 | ADVANCES IN SWARM INTELLIGENCE, ICSI 2017, PT I |
Keywords | Field | DocType |
Fruit fly optimization,Function optimization,Disturbance mechanism | Mathematical optimization,Computer science,Local optimum,Function optimization,Optimization algorithm,Jump | Conference |
Volume | ISSN | Citations |
10385 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 4 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kejie Wang | 1 | 0 | 0.68 |
| Hui-Ling Chen | 2 | 655 | 26.09 |
| Qiang Li | 3 | 4 | 0.80 |
| Junjie Zhu | 4 | 2 | 1.82 |
| Shubiao Wu | 5 | 0 | 0.34 |
| Hui Huang | 6 | 0 | 0.34 |