A linguistic multicriteria analysis system combining fuzzy sets theory, ideal and anti-ideal points for location site selection

Most multicriteria methods try to model human thinking and insert the results of this modelling into their procedures. Following this path, the proposed multicriteria approach first captures the imprecision and vagueness of data by using linguistic variables. At a second level, it utilises human processes of decision-making by creating decision rules and modelling them with functions used in fuzzy sets theory. This method also is compatible with the way fuzzy logic models and combines fuzzy propositions. The proposed method considers the ideal solution and the anti-ideal solution and assesses each alternative in terms of distance as well as similarity to the ideal solution and the anti-ideal solution. Distance and similarity measures for fuzzy numbers are used and their aggregation is guided by the decision rules in order to construct decision functions. Further, OWA operators with maximal entropy are used to aggregate across all criteria and determine the overall score of each alternative. It is shown that the proposed method presents flexibility in modelling the decision maker’s preferences and it is also appropriate and effective to handle multicriteria problems of considerable complexity.