Extended QUALIFLEX method for electronic music acoustic quality evaluation based on the picture fuzzy multiple attribute group decision making

Article type: Research Article

Authors: Yang, Run^{; *}

Affiliations: Jiamusi University, Jiamusi, Heilongjiang, China

Correspondence: [*] Corresponding author. Run Yang, Jiamusi University, Jiamusi, 154007, Heilongjiang, China. E-mail: 2015223030088@stu.scu.edu.cn; E-mail: yangrun1981@163.com.

Abstract: In the past, different useful extensions of fuzzy sets were established by the researchers to manage the vagueness and uncertainty in various practical problems. Usually, the real numbers are utilized to express the decision information, but it is noted that the description of attributes using picture fuzzy sets (PFSs) proves to be more appropriate. As a powerful decision tool, PFSs provides more decision information that requires the application of some specific situations more types of response of human ideas: yes, contain, no, reject. QUALIFLEX (qualitative flexible multiple criteria method), is one of the well-known outranking methods to solve the multiple attribute group decision making (MAGDM) problems with crisp numbers. The QUALIFLEX method can perfectly address the complex MAGDM problems where a lot of attributes are utilized to assess a limited number of alternatives. The electronic music acoustic quality evaluation is a classical MAGDM. This paper proposes and utilizes the QUALIFLEX to develop the picture fuzzy QUALIFLEX(PF-QUALIFLEX) method for MAGDM. The current study is mainly devoted to explore and extend the measurement of alternatives and ranking according to the QUALIFLEX under the background of PFSs. Furthermore, an example to evaluate the electronic music acoustic quality is handled through the proposed method to substantiate the extended approach.

Keywords: Multiple attribute group decision making (MAGDM), picture fuzzy sets (PFSs), the extended QUALIFLEX method, electronic music acoustic quality evaluation

DOI: 10.3233/JIFS-223377

Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 5021-5032, 2023