Localized probability of improvement for kriging based multi-objective optimization
The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationall...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2017-12-01
|
| Series: | Open Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/phys-2017-0117 |
| Summary: | The paper introduces a new approach to kriging based multi-objective optimization by utilizing a local probability of improvement as the infill sampling criterion and the nearest neighbor check to ensure diversification and uniform distribution of Pareto fronts. The proposed method is computationally fast and linearly scalable to higher dimensions. |
|---|---|
| ISSN: | 2391-5471 |