Name
Abstract | ||
|---|---|---|
Tuning various parameters coexisting in genetic algorithms (GAs) has a direct impact on the performance of GA. Because of this, finding a proper parameter value is challenging. In this study, we use support vector regression to show the appropriate parameter space of GA. Moreover, this was applied and analyzed to solving NK-landscape problems. As a result, we show the complexities and difficulties of GA parameter space through this paper.
|
Year | Venue | Field |
|---|---|---|
2018 | GECCO (Companion) | Mathematical optimization,Computer science,Support vector machine,Parameter space,Genetic algorithm |
DocType | ISBN | Citations |
Conference | 978-1-4503-5764-7 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hwi-Yeon Cho | 1 | 0 | 1.35 |
| Hye-Jin Kim | 2 | 39 | 17.46 |
| Yong-Hyuk Kim | 3 | 355 | 40.27 |