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Table 1 Examples of software and algorithms used in spatial MCDA problem settings

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 Chen et al., 2001 [25], Lim & Lee, 2009 [28]
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]
  1. Note: algorithms listed above are generally used in problems of discrete nature. Different algorithms exist for problems with a continuous nature.