Multi-Criteria Decision Analysis

Methods for analysis of complex decision problems involving noncommensurable, conflicting criteria on the basis of which alternative decisions are evaluated. The term multicriteria decision analysis (MCDA) is used interchangeably with multicriteria decision making (MCDM). Broadly speaking, MCDA problems involve a set of alternatives that are evaluated on the basis of conflicting and incommensurate criteria. Criterion is considered a generic term that includes both the concepts of attributes and objective. Accordingly, two broad classes of MCDA can be distinguished: MADA (multiattribute decision analysis) and MODA (multiobjective decision analysis). Both MADA and MODA problems are further categorized into single-decision-maker problems and group decision problems. These two categories are, in term, subdivided into deterministic, probabilistic, and fuzzy decision. Deterministic decision problems assume that the required data and information are known with certainty and that there is a known deterministic relationship between every decision and the corresponding decision consequence. Probabilistic analysis deals with a decision situation under uncertainly about the state of the problem environment and about the relationship s between the decision and its consequences. Whereas probabilistic analysis treats uncertainly as randomness, it is also appropriate to consider inherent imprecision of information involved in decision making; fuzzy decision analysis deals with this type of uncertainty. Conventional MCDA techniques have largely been aspatial in the sense that they assume a spatial homogeneity within the study area. This assumption is unrealistic in many decision situations because the evaluation criteria vary across space. Consequently, there is a need for an explicit representation of the geographical dimension in MCDA.