Infinitesimal perturbation analysis for general discrete event systems
Journal of the ACM (JACM)
Likelihood ratio gradient estimation for stochastic systems
Communications of the ACM - Special issue on simulation
Recent advances in simulation for security pricing
WSC '95 Proceedings of the 27th conference on Winter simulation
Simulation optimization: methods and applications
Proceedings of the 29th conference on Winter simulation
An overview of derivative estimation
WSC '91 Proceedings of the 23rd conference on Winter simulation
Simulation optimization: a survey of simulation optimization techniques and procedures
Proceedings of the 32nd conference on Winter simulation
Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Gradient-based simulation optimization
Proceedings of the 38th conference on Winter simulation
Efficient stochastic sensitivity analysis of discrete event systems
Journal of Computational Physics
Recent advances in simulation for security pricing (1995)
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
| Hi-index | 0.00 |
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.