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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.