Introductory Tutorial: Simulation Optimization under Input Uncertainty

Abstract

Input uncertainty in the simulation output is caused by the estimation error in the input models of the simulator due to finiteness of the data from which they are estimated. Ignoring input uncertainty when formulating and solving a simulation optimization problem may lead to a solution with poor system performance. This tutorial discusses how to incorporate input uncertainty in simulation optimization to avoid such risk. We first categorize the problems into three groups based on their contexts: fixed batch data, streaming data, and active input data collection problems. Input and simulation output response modeling frameworks that can be adopted in all three categories are discussed. Then, we provide a high-level overview of simulation optimization problem formulations and algorithmic approaches to tackle problems in each group. Some thoughts on future research directions are shared.

Citation

@inproceedings{he2024introductory,
  title={Introductory tutorial: simulation optimization under input uncertainty},
  author={He, Linyun and Song, Eunhye},
  booktitle={2024 Winter Simulation Conference (WSC)},
  pages={1338--1352},
  year={2024},
  organization={IEEE}
}