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Article type: Research Article
Authors: Zhang, Yangjingyua; * | Cai, Qiangb | Wei, Guiwua; b | Chen, Xudongc; *
Affiliations: [a] School of Mathematical Sciences, Sichuan Normal University, Chengdu, P.R. China | [b] School of Business, Sichuan Normal University, Chengdu, P.R. China | [c] School of Accounting, Southwestern University of Finance and Economics, Chengdu, P.R. China
Correspondence: [*] Corresponding author. Yangjingyu Zhang, School of Mathematical Sciences, Sichuan Normal University, Chengdu, 610101, P.R. China. E-mail: 1142608818@qq.com and Xudong Chen, School of Accounting, Southwestern University of Finance and Economics, Chengdu, 610074, P.R.China. E-mail: xutung99@126.com.
Abstract: Based on the traditional TOPSIS method and 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs), this paper builds a novel 2TLPF-TOPSIS method that combines cumulative prospect theory (CPT) to cope with the multiple attribute group decision-making (MAGDM). This new method takes into account the decision-makers’ mind and the uncertainty of decision-making, and is more in line with the real decision-making environment. First, this paper briefly reviews some necessary theories related to PFS, as well as the calculation rules and comparison methods of 2TLPFNs. Then, since there is often subjective randomness when determining the weight, the entropy method is utilized to objectively determine the weight. After that, give the specific calculation steps of the new method. In order to show the effectiveness of the new method, apply it into a specific numerical example about evaluating airline business operations capability, and compare it with the other four different methods. The ranking results depict that the new method designed is effective and reasonable, and has good application value of MAGDM problems.
Keywords: Multiple attribute group decision making (MAGDM), 2-tuple linguistic Pythagorean fuzzy numbers (2TLPFNs), TOPSIS method, cumulative prospect theory (CPT), airline business operations capability
DOI: 10.3233/JIFS-220776
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 4, pp. 5745-5758, 2023
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