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)|
|Number of pages||12|
|State||Published - 2016|
All Science Journal Classification (ASJC) codes
- Information Systems
- Applied Mathematics
- statistical models