Global Optimization under Non-Convex Constraints — The Index Approach
Part of the Nonconvex Optimization and Its Applications book series (NOIA, volume 45)
- 480 Downloads
Consider the constrained global minimization problemwhere the objective function φ, henceforth denoted g m +1, i.e., g m +1(x) = φ(x), and left-hand sides g i , 1 ≤ i ≤ m, of the constraints are assumed to be Lipschitzian respectively with constants L i , 1 ≤ i ≤ m + 1, and, in general, are multi-extremal.
KeywordsObjective Function Global Optimization Limit Point Convergence Condition Trial Point
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Unable to display preview. Download preview PDF.
© Springer Science+Business Media Dordrecht 2000