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This means that criteria and preference information can be uncertain, inaccurate or partially missing. Incomplete information is represented in SMAA using suitable probability distributions. The method is based on stochastic simulation by drawing random values for criteria measurements and weights
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Sousa R., Yevseyeva I., Pinto da Costa J.F., Cardoso J.S. (2013). Multicriteria models for learning ordinal data: A literature review. In Yang X.S. Artificial
Intelligence, Evolutionary Computing and Metaheuristics: In the Footsteps of Alan Turing. Studies in Computational Intelligence 427,
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Lahdelma, R.; Salminen, P. (2001). "SMAA-2: Stochastic
Multicriteria Acceptability Analysis for Group Decision Making".
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information. Ordinal information is treated by a special joint distribution that preserves the ordinal information.
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Tervonen, T.; Figueira, J. (2008). "A survey on stochastic multicriteria acceptability analysis methods".
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A survey on different variants and applications of SMAA can be found in this article.
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Open source implementations of SMAA can be found at the website SMAA.fi.
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146:"Open source decision aiding software for real-life applications"
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method for problems with missing or incomplete information.
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17:Stochastic multicriteria acceptability analysis
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119:Journal of Multi-Criteria Decision Analysis
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187:Multiple-criteria decision analysis
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94:10.1287/opre.49.3.444.11220
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182:Mathematical optimization
39:SMAA can handle mixed
72:Operations Research
177:Decision analysis
144:Tervonen, Tommi.
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31:Description
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Text is available under the Creative Commons Attribution-ShareAlike License. Additional terms may apply.