2000Journal of Northeastern UniversityRequires access

Multiple Attribute Decision Making Method with the Fuzzy Preference Relation

Fan Zhi

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Abstract

A new multiple attribute decision making method was presented for ranking alternatives based on fuzzy preference relation about the alternatives provided by the decision maker. A linear goal programming model was constructed to determine the weight vector of attributes and to rank the alternatives. In this model,the ranking of alternatives incarnates an aggregation of the preference information about the alternatives and the decision matrix,and reflects the subjective preference of the decision maker. Finally, a numerical example was used to illustrate the use of the proposed method.

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What this paper is about

A new multiple attribute decision making method was presented for ranking alternatives based on fuzzy preference relation about the alternatives provided by the decision maker. A linear goal programming model was constructed to determine the weight vector of attributes and to rank the alternatives. In this model,the ranking of alternatives incarnates an aggregation of the preference information about the alternatives and the decision matrix,and reflects the subjective preference of the decision maker. Finally, a numerical example was used to illustrate the use of the proposed method.

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Available abstract

A new multiple attribute decision making method was presented for ranking alternatives based on fuzzy preference relation about the alternatives provided by the decision maker. A linear goal programming model was constructed to determine the weight vector of attributes and to rank the alternatives. In this model,the ranking of alternatives incarnates an aggregation of the preference information about the alternatives and the decision matrix,and reflects the subjective preference of the decision maker. Finally, a numerical example was used to illustrate the use of the proposed method.

Key concepts: Preference, Ranking (information retrieval), Preference relation, Relation (database), Decision maker, Rank (graph theory), Preference learning, Mathematics

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