Abstract
The TODIM is a decision-making method that can examine the psychological behavior of decision-makers (DMs). However, the traditional TODIM method has still not been having the ability to overcome fuzzy information such as interval values and linguistic variables. This paper proposes an extended TODIM decision-making model for multiple-attribute decision-making (MADM) problems in a linguistic environment using dual-connection numbers (DCNs). The extended model uses linguistic variables in which the values of alternatives and criteria for both of them are formatted in the triangular fuzzy numbers (TFNs) to express the uncertain information. First, some definitions and basic operators of the TFNs and DCNs are introduced. Then, the way how to convert fuzzy information in forms of the TFNs into DCNs and the step how to transform each criterion weight value into a crisp value using the defuzzification of Minkowski are demonstrated. Furthermore, the traditional TODIM is improved to address MADM problems with DCNs, and detailed calculation steps in determining decisions are explained. Finally, an illustrative example which is a cadre selection problem is applied to demonstrate the conformity and validity of the extended TODIM method and to compare it with some other methods.
Highlights
Multiple-attribute decision-making (MADM) has become a principal issue in decision science. is approach can determine the best and optimal alternatives from a finite set of alternatives
Results and Discussion is section will show the results presented by using an illustrative example and compared to the obtained results of [12, 27]
An Illustrative Example. is subsection will explain how the proposed fuzzy TODIM can be suitably applied to a cadre selection problem for an organization in China as obtained in [12]. e organization had to assess cadres based on six criteria: morality and ideology (AT1), working attitude (AT2), work custom (AT3), level of education and structure of knowledge (AT4), leadership (AT5), and ability of exploitation (AT6)
Summary
Multiple-attribute decision-making (MADM) has become a principal issue in decision science. is approach can determine the best and optimal alternatives from a finite set of alternatives. In many real decision-making processes, the assessment information and DM’s judgment preferences may be in the form of linguistic variables and under fuzzy environment In this kind of case, these two pieces of information can be expressed in terms of fuzzy sets such as TFNs, Pythagorean fuzzy numbers, and TrFNs. In this study, we utilize the characteristic of TFNs to convert the information-processing problem of TFNs to the information-processing problem of DCNs. is step guides us to obtain the DCN distance. Because of the limited rationality of DMs and dissimilar preferences when addressing gain and loss, the TODIM method is applied to be a suitable instrument that can advise an appropriate selection and an optimum satisfaction for DMs. DCNs are able to represent uncertain and certain information but they can analyze characteristics, interrelation, and a relation of these two pieces of information.
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