## 4 Discussion
### MCDA as Decision-Making Options for Computational Models
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**Method** & **Advantages** & **Disadvantages** & **Uses** \\ \hline \multirow{4}{*}{Equal weighting} & Easiest of all methods & Few if any real world scenarios have & \\  & Easiest of all methods & all attributes of & Early in the decision process \\  & Easily implemented with & equal importance & \\  & Easily implemented with & Inaccurate relative to & Situations with incomplete \\  & spreadsheet or calculator & other techniques & or no attribute information \\  & & & Scenarios where a large number \\  & & & of attributes are present \\ \hline \multirow{4}{*}{Rank Ordered Centroid} & Uses ordinal ranking only & \multirow{2}{*}{Based on uniform distribution} & Analy is unwilling \\  & to determine weights & & design specifics weights \\  & Easily implemented with & & Scenarios when consensus may not be \\  & spreadsheet or calculator & & necessary or desirable, \\  & & & but ranking can be agreed upon [80] \\  & & & Scenarios where a large \\  & & & number of attributes are present \\ \hline \multirow{4}{*}{Rank Sum} & Uses ordinal ranking only & \multirow{2}{*}{Based on uniform distribution} & Analyst is unwilling to \\  & to determine weights & & assign specifics weights \\  & Easily implemented with & & Scenarios when consensus may not be \\  & spreadsheet or calculator & & necessary or desirable, \\  & & & be agreed upon [80] \\  & & & Scenarios where a large \\  & & & number of attributes are present \\ \hline \multirow{4}{*}{Rank Reciprocal} & Uses ordinal ranking only & Only useful when more precise & Analyst is unwilling to \\  & to determine weights & weighting is not available & assign specific weights \\  & Easily implemented with & & Scenarios when consensus may not be \\  & spreadsheet or calculator & & necessary or desirable, \\  & & & but ranking can be agreed upon [80] \\  & & & Scenarios where a large \\  & & & number of attributes are present \\ \hline \multirow{4}{*}{Rank Reciprocal} & Uses ordinal ranking only & Only useful when more precise & Analyst is unwilling to \\  & to determine weights & weighting is not available & \\  & & & assign specific weights \\  & Easily implemented with & & Scenarios when consensus may not be \\  & & & necessary or desirable, \\  & spreadsheet or calculator & & but ranking can be agreed upon [80] \\  & & & Scenarios where a large \\  & & & number of attributes are present \\ \hline \end{tabular}
\end{table} 
Table 17: Characteristics of weighting methods for approximate techniques. The applicability of the ratio assignment and approximate techniques differ based on the context of the problem being addressed, the decisions being made, the decision makers being modeled, and the criterion that have been deemed necessary for a given decision. We provide an overview of the components within ABM, SD, and DES that are relevant to implementing these techniques within a simulation model. Table 18 provides a comparison of ratio assignment techniques and Table 19 provides a comparison of approximate techniques. These tables are intended to provide guidance and initial steps towards incorporating MCDA techniques. These are not intended to be exhaustive comparisons. Determining the appropriate MCDA technique to select is highly dependent upon the given system context, the outcomes being examined, any performance metrics being assessed, the level of aggregation desired, and many other potential criteria. The criteria that are involved in the weighting combinations serve as candidates that should be involved in the verification and validation stages of model development and testing. For verification, the implementation of the criteria should be traceable back to the MCDA technique identified in the model design. This should be checked for consistency against the subject matter experts' specifications or any other conceptual model documentation. For validation, the selected MCDA categorization as well as the specific technique and its method for distributing weights, should be checked against what is known about the system.