Multiplicative Consistency and DEA Cross-Efficiency-Driven Decision-Making Method with Fuzzy Preference Relations

Owing to the uncertainty and vagueness of practical decision-making problems, it is more convenient for decision-makers (DMs) to express evaluation information with fuzzy preference relations (FPRs) than precise numerical values. As two important issues in the decision-making process with FPRs, improving consistency and acquiring the priority weights are worth further studying. In this paper, we first provide an approach for constructing the FPR with multiplicative consistency, and then an algorithm of improving consistency is presented to generate an acceptable FPR, in which the initial evaluation information is retained to the largest extent through the local adjustment strategy. Then, an input-oriented CCR DEA model is developed to derive the priority weight vector of alternatives, which is followed that a DEA cross-efficiency model is constructed to discriminate multiple DEA efficient DMUs. Subsequently, the complete rankings of alternatives can be generated by a novel DEA-driven decision-making method. Finally, a numerical example is proposed to verify the feasibility and effectiveness of the developed method. The advantages of the developed method are performed by comparative analysis and sensitivity analysis.