We consider the intrinsic difficulty of global optimization in high dimensional Euclidean space. We adopt an asymptotic analysis, and give a lower bound on the number of function evaluations required to obtain a given error tolerance. This lower bound complements upper bounds provided by recently proposed algorithms.
|Original language||English (US)|
|Number of pages||10|
|Journal||Springer Optimization and Its Applications|
|State||Published - Jan 1 2016|
All Science Journal Classification (ASJC) codes
- Control and Optimization