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A constrained simultaneous perturbation stochastic approximation algorithm based on penalty functions

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2 Author(s)
I. -J. Wang ; Appl. Phys. Lab., Johns Hopkins Univ., MD, USA ; J. C. Spall

We present a stochastic approximation algorithm based on the penalty function method and a simultaneous perturbation gradient estimate for solving stochastic optimization problems with general inequality constraints. We also presents a very general convergence result for the proposed algorithm

Published in:

Intelligent Control (ISIC), 1998. Held jointly with IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA), Intelligent Systems and Semiotics (ISAS), Proceedings

Date of Conference:

14-17 Sep 1998