Document Type


Publication Date




Publication Title

Applied Sciences






10397 (1-29)


Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.


© 2021 by the authors.

This is an open access article distributed under the Creative Commons Attribution 4.0 International (CC BY 4.0) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Original Publication Citation

Ezell, B., Lynch, C. J., & Hester, P. T. (2021). Methods for weighting decisions to assist modelers and decision analysts: A review of ratio assignment and approximate techniques. Applied Sciences, 11(21), 1-29, Article 10397.


0000-0003-4274-908X (Ezell), 0000-0002-4830-7488 (Lynch)