Global Optimization with Non-Convex Constraints 豆瓣
作者:
Strongin, Roman G.; Strongin, R. G.; Sergeyev, Y. D.
2000
- 10
This book presents a new approach to global non-convex constrained optimization. Problem dimensionality is reduced via space-filling curves. To economize the search, constraint is accounted separately (penalties are not employed). The multicriteria case is also considered. All techniques are generalized for (non-redundant) execution on multiprocessor systems. Audience: Researchers and students working in optimization, applied mathematics, and computer science.