Document Type
Article
Publication Date
2017
DOI
10.1016/j.eswa.2017.08.003
Publication Title
Expert Systems with Applications
Volume
90
Pages
111-126
Abstract
Decision makers often face complex problems, which can seldom be addressed well without the use of structured analytical models. Mathematical models have been developed to streamline and facilitate decision making activities, and among these, the Analytic Hierarchy Process (AHP) constitutes one of the most utilized multi-criteria decision analysis methods. While AHP has been thoroughly researched and applied, the method still shows limitations in terms of addressing user profile disparities. A novel sensitivity analysis method based on local partial derivatives is presented here to address these limitations. This new methodology informs AHP users of which pairwise comparisons most impact the derived weights and the ranking of alternatives. The method can also be applied to decision processes that require the aggregation of results obtained by several users, as it highlights which individuals most critically impact the aggregated group results while also enabling to focus on inputs that drive the final ordering of alternatives. An aerospace design and engineering example that requires group decision making is presented to demonstrate and validate the proposed methodology.
Original Publication Citation
Ivanco, M., Hou, G., & Michaeli, J. (2017). Sensitivity analysis method to address user disparities in the analytic hierarchy process. Expert Systems with Applications, 90, 111-126. doi:10.1016/j.eswa.2017.08.003
ORCID
0000-0002-7352-1099 (Hou)
Repository Citation
Ivanco, Marie; Hou, Gene; and Michaeli, Jennifer, "Sensitivity Analysis Method to Address User Disparities in the Analytic Hierarchy Process" (2017). Mechanical & Aerospace Engineering Faculty Publications. 45.
https://digitalcommons.odu.edu/mae_fac_pubs/45
Included in
Artificial Intelligence and Robotics Commons, Electrical and Computer Engineering Commons, Mechanical Engineering Commons, Operational Research Commons
Comments
This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/)