Document Type
Conference Paper
Publication Date
2009
Publication Title
Proceedings of the 2009 Summer Computer Simulation Conference
Pages
291-298
Conference Name
2009 Summer Computer Simulation Conference, July 13-16, 2009, Istanbul, Turkey
Abstract
In this paper, a framework for conducting Sensitivity Analysis (SA) on large and complex simulation models is introduced. The framework consists of components that are designed to make the SA a systematic process that is easy to manage and follow by simulation analysts and practitioners. Unlike local SA (one-variable-at-a-time SA), the method presented here is variance-based and it is rooted in the field of Design of Experiments (DoE) where Input Variables are varied and Output Variables are measured. Based on the DoE results, a risk scoring system is developed to identify the sensitivity of the Input Variables, and as a result classify them into High, Medium, and Low risk variables. As such, decision makers can be aware of the most sensitive high-risk input variables in a simulation model to ensure they understand the value of data reliability in their model inputs.
ORCID
0000-0001-8145-313X (Rabadi), 0000-0001-9452-9105 (Keating)
Original Publication Citation
Rabadi, G., Bowling, S., Keating, C. & Unal, R. (2009) Sensitivity analysis framework for large and complex simulation models. Proceedings of the 2009 Summer Computer Simulation Conference (pp. 291-298). Simulation Councils, Inc.
Repository Citation
Rabadi, Ghaith; Bowling, Shannon; Keating, Charles; and Unal, Resit, "Sensitivity Analysis Framework for Large and Complex Simulation Models" (2009). Engineering Management & Systems Engineering Faculty Publications. 95.
https://digitalcommons.odu.edu/emse_fac_pubs/95
Comments
© 2009 Simulation Councils, Inc., now Society for Modeling and Simulation International.
Included with the kind written permission of the publisher.