The THOR method and fuzzy theory
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Once instigated by the need for improvement of the multicriteria algorithm for decision support THOR, with respect to data input by the decision maker, a new proposal with the inclusion of fuzzy theory was developed. In this sense, aiming to ease the cognitive effort that the decision maker needs when using the THOR algorithm, a fuzzy scale was designed, allowing the decision maker to express only a single value judgment. The study conducted on the THOR methodology suggests that, the inclusion of fuzzy theory, from three steps, fuzzification, inference and defuzzification is able to sort and m...
Once instigated by the need for improvement of the multicriteria algorithm for decision support THOR, with respect to data input by the decision maker, a new proposal with the inclusion of fuzzy theory was developed. In this sense, aiming to ease the cognitive effort that the decision maker needs when using the THOR algorithm, a fuzzy scale was designed, allowing the decision maker to express only a single value judgment. The study conducted on the THOR methodology suggests that, the inclusion of fuzzy theory, from three steps, fuzzification, inference and defuzzification is able to sort and model imprecision more robustly. To test the THOR algorithm with fuzzy input data, a case study from the opinion of experts from private companies, operating in the public wharf of the Port of Rio Grande / RS, on the port performance indicators with respect to the economy of services provided to ships, was performed. The results obtained showed great relevance for the port action plan. Furthermore, the results of the computational tests when compared to other versions of THOR are encouraging.
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