Stochastic Gradient Estimation
Fu, Michael C.
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We consider the problem of efficiently estimating gradients from stochastic simulation. Although the primary motivation is their use in simulation optimization, the resulting estimators can also be useful in other ways, e.g., sensitivity analysis. The main approaches described are finite differences (including simultaneous perturbations), perturbation analysis, the likelihood ratio/score function method, and the use of weak derivatives.
This is a pre-print version of Chapter 19 in Handbooks in Operations Research and Management Science: Simulation, S.G. Henderson and B.L. Nelson, eds., Elsevier.