Title: Global Optimization with Non-Convex Constraints
Description: 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.
Subjects: Algorithms, Mathematics, Information theory, Computer science, Mathematical optimization, Engineering, Optimization, Computational Mathematics and Numerical Analysis, Theory of Computation, Engineering, general