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- W2130584997 abstract "In this paper, we discuss some research issues related to the general topic of optimizing a stochastic system via simulation. In particular, we devote extensive attention to finite-difference estimators of objective function gradients and present a number of new limit theorems. We also discuss a new family of orthogonal function approximations to the global behavior of the objective function. We show that if the objective function is sufficiently smooth, the convergence rate can be made arbitrarily close to n-1/2 in the number of observations required. The paper concludes with a brief discussion of how these ideas can be integrated into an optimization algorithm." @default.
- W2130584997 created "2016-06-24" @default.
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- W2130584997 date "1989-01-01" @default.
- W2130584997 modified "2023-10-16" @default.
- W2130584997 title "Optimization of stochastic systems via simulation" @default.
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- W2130584997 doi "https://doi.org/10.1145/76738.76750" @default.
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