Article ID: | iaor20172750 |
Volume: | 254 |
Issue: | 1 |
Start Page Number: | 425 |
End Page Number: | 447 |
Publication Date: | Jul 2017 |
Journal: | Annals of Operations Research |
Authors: | Tsai Shing, Yang Tse |
Keywords: | optimization, stochastic processes, statistics: sampling, statistics: empirical |
A simulation optimization framework containing three fundamental stages (feasibility check, screening, and selection) is proposed for solving the zero‐one optimization via simulation problem in the presence of a single stochastic constraint. We present three rapid screening algorithms that combine these three stages in different manners, such that various sampling mechanisms are applied, therefore yielding different statistical guarantees. An empirical evaluation for the efficiency comparison between the proposed algorithms and other existing works is provided.