Abstract
This paper reviews the interplay between global optimization and probability models, concentrating on a class of deterministic optimization algorithms that are motivated by probability models for the objective function. Some complexity results are described for the univariate and multivariate cases.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 323-334 |
| Number of pages | 12 |
| Journal | Informatica (Netherlands) |
| Volume | 27 |
| Issue number | 2 |
| DOIs | |
| State | Published - 2016 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Information Systems
- Applied Mathematics
Keywords
- convergence
- optimization
- statistical models