Abstract
This paper proposed a new multiattribute group decision-making method, in which the period significance coefficients and the attribute significance coefficients are completely unknown, and the attribute values are triangular fuzzy numbers. At first, to obtain the period significance coefficients, the period significance coefficients optimization model is constructed according to the time degree and the differences of the decision information in different periods. Then, attribute significance coefficients are determined by the maximum deviation method. Based on this, alternatives are ranked by the triangular fuzzy ratio system method, the triangular fuzzy reference point method, and the triangular fuzzy full multiplicative form, respectively. The dominance theory is used for aggregating the subordinate rankings into the final ranking. Finally, a numerical example is presented to illustrate the feasibility and effectiveness of the proposed method.
Highlights
Multiattribute decision-making (MADM) has been widely used in many practical problems, such as emergency plan selection, supplier selection, consumer purchasing selection, and human resource management
This paper proposed a new multiattribute group decision-making method, in which the period significance coefficients and the attribute significance coefficients are completely unknown, and the attribute values are triangular fuzzy numbers
We developed a novel extension of MULTIMOORA method based on considering the current and historical information to solve multiattribute group decision-making (MAGDM) problems
Summary
Multiattribute decision-making (MADM) has been widely used in many practical problems, such as emergency plan selection, supplier selection, consumer purchasing selection, and human resource management. In the practical decision, they are partly known, even completely unknown To deal with these problems, many fuzzy decision methods and stochastic decision methods are proposed. Few studies extended MULTIMOORA into the triangular fuzzy number environment and obtained the final ranking by the dominance theory. Balezentis et al [27] extended MULTIMOORA based on the triangular fuzzy number. They only considered the current decision information and ignored the importance of the historical information. We developed a novel extension of MULTIMOORA method based on considering the current and historical information to solve MAGDM problems. The major contribution of our proposed method is that it considered the current and the historical information of the decision object.
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