The basis for decision making is that given two objects, say A and B, people can meaningfully say whether they prefer A to B, B to A or whether they are indifferent (von Winterfeldt and Edwards 1986). Usually, it is assumed that people can also state the strength of this preference. The strength could be expressed either in ordinal terms, or in cardinal terms. If the decision maker can say that change from A to B is preferable to change from B to C, then the judgment is ordinal. If the decision maker can say by how much, the judgment is cardinal.
Multi-Attribute Utility Theory, where the utility of the decision maker is considered to consist of several attributes, is usually shortened with MAUT. In different contexts, concepts ‘objectives’ and ‘criteria’ are used instead of ‘attributes’. Malczewski (1999, p. 85) defines multi-criteria decision making as a broader class, which includes both multi-attribute decision making for discrete decision problems and multi-objective decision making for continuous problems. He defines attributes as measures of performance of an object, and objects as statements about the desired state of a system. In this book, the attributes and criteria are used as synonyms, and multi-objective is only used in the context of optimization.
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Keywords
- Utility Function
- Analytic Hierarchy Process
- Analytic Network Process
- Decision Attribute
- Fuzzy Analytic Hierarchy Process
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(2008). Multi-Criteria Decision Problems. In: Decision Support for Forest Management. Managing Forest Ecosystems, vol 16. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-6787-7_3
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