Retrospective simulation response optimization

Abstract

An approach to simulation response optimization in which a simulation experiment is run in such a manner as to generate optimal solutions is presented. Once the stochastic sample path of a simulation run has been generated, it is sometimes possible to retrospectively solve a deterministic optimization problem or a closely related problem. As demonstrated with some examples from communications and manufacturing, this approach can greatly simplify both the simulation experiment and the simulation model. >