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Simultaneous perturbation stochastic approximation (SPSA) is an algorithmic method for optimizing systems with multiple unknown parameters. It is a type of stochastic approximation algorithm. As an optimization method, it is appropriately suited to large-scale population models, adaptive modeling, simulation optimization, and atmospheric modeling. Many examples are presented at the SPSA website [1].

References

• Hirokami, T., Maeda, Y., Tsukada, H. (2006) "Parameter estimation using simultaneous perturbation stochastic approximation", Electrical Engineering in Japan, 154 (2), 30–3 http://dx.doi.org/10.1002/eej.20239

• Spall, J.C. (1998). "Overview of the Simultaneous Perturbation Method for Efficient Optimization" [2]. Johns Hopkins APL Technical Digest, 19(4), 482–492.

• Spall, J.C. (2003) Introduction to stochastic search and optimization: estimation, simulation, and control, Wiley. ISBN 0471330523 (Chapter 7)