Least squares approach to constrained global optimization
Mohamed Ali Zohdy, Bogdan Adamczyk · 2002
The authors present a stochastic least squares approach to the problem of determining the global extremum of multivariable nonlinear objective functions subject to constraints. The approximate value of the global extremum is found by using a special transformation followed by least squares estimation. The corresponding optimal coordinates are derived by a neural network.>