Title :
Least squares approach to constrained global optimization
Author :
Zohdy, Mohamed A. ; Adamczyk, Bogdan
Author_Institution :
Dept. of Electr. & Syst. Eng., Oakland Univ., Rochester, MI, USA
Abstract :
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
Keywords :
least squares approximations; neural nets; optimisation; constrained global optimization; global extremum; multivariable nonlinear objective functions; neural network; stochastic least squares approach; Constraint optimization; Least squares approximation; Least squares methods; Multi-layer neural network; Neural networks; Neurons; Parameter estimation; Stochastic processes; Stochastic systems; Systems engineering and theory; Vectors;
Conference_Titel :
Decision and Control, 1991., Proceedings of the 30th IEEE Conference on
Conference_Location :
Brighton
Print_ISBN :
0-7803-0450-0
DOI :
10.1109/CDC.1991.261463
