Title :
Global optimization of stochastic multivariable functions
Author :
Zohdy, M.A. ; Khan, Aftab Ali ; Kamel, M.S.
Author_Institution :
Dept. of Electr. & Syst. Eng., Oakland Univ., Rochester, MI, USA
Abstract :
This paper presents a new methodology for global optimization of a stochastic multivariable functions subject to stochastic, possibly nonlinear constraints. Least squares parametric estimation is applied as an intermediate step in the stochastic optimizer which then uses a special transformation to capture the global optima estimate. A comparative study of implementing estimation in polynomial least squares versus spline fitting is also presented, together with an illustrative example
Keywords :
least squares approximations; optimisation; parameter estimation; stochastic processes; global optima estimate; global optimization; least squares parametric estimation; nonlinear constraints; polynomial least squares; spline fitting; stochastic multivariable functions; Clustering methods; Least squares approximation; Noise generators; Noise measurement; Optimization methods; Polynomials; Spline; State estimation; Stochastic processes; Vectors;
Conference_Titel :
System Theory, 1994., Proceedings of the 26th Southeastern Symposium on
Conference_Location :
Athens, OH
Print_ISBN :
0-8186-5320-5
DOI :
10.1109/SSST.1994.287859
