Optimization of Stochastic Systems via Simulation

P. W. Glynn

Proceedings of the 1989 Winter Simulation Conference, 90-105 (1989)

In this paper, we discuss some research issues rdated to the general topic of optimizing a stochastic system via simulation. In particular, we devote extensive attention to finitedifference 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 observatious required. The paper concludes with a brief discussion of how these ideas can be integrated into an optimization algorithm.