From: Spatially explicit multi-criteria decision analysis for managing vector-borne diseases
Example decision rules/algorithms | Algorithm strengths | Compatible software packages | Example applications |
---|---|---|---|
Analytical Hierarchy Process-specific adaptation of the weighted linear combination method | Multiobjective, multicriteria decision making approach that employs pair-wise comparison procedure to arrive at a scale of preference among a set of alternatives | ArcGIS (ESRI), IDRISI (Clark Labs, Worcester, MA), MultCSynch software package | Aceves-Quesada et al., 2006 [23], Akgun & Turk, 2010 [21], Rakotomanana et al., 2007 [18], Sarkar et al., 2010 [19], Vadrevu et al., 2010 [22] |
Compromise programming and spatial compromise programming | Identifies solutions based on their deviations from the ideal solution | ArcGIS (ESRI), MCE-RISK | |
Dempster-Shafer theory | Capable of representing uncertainty based on probability distributions | IDRISI (Clark Labs, Worcester, MA) | Clements et al., 2006 [17] |
Fuzzy multicriteria decision-making | Can accommodate non-crisp data | ArcGIS (ESRI) | Chang et al., 2008 [29] |
Ordered weighted averages | Provides mechanism to compensate for criteria with low scores via criteria with higher scores | IDRISI (Clark Labs, Worcester, MA) | Clements et al., 2006 [17] |
Technique for order preference by similarity to ideal solution | Provides mechanism to compensate for criteria with low scores via other criteria with higher scores | MCE-RISK | Chen et al., 2001 [25] |
Weighted linear combination and multicriteria evaluation for weighted linear combination | Fully compensatory model, thought to better represent uncertainty in near-ignorance situations [17]; multicriteria evaluation uses a pairwise comparison method which provides an assessment of the degree of consistency among weightings [31] | IDRISI (Clark Labs, Worcester, MA), MCE-RISK | Akgun et al., 2008 [20], Chen et al., 2001 [25], Clements et al., 2006 [17], Rakotomanana et al., 2007 [18], Symeonakis et al., 2007 [31] |