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Article type: Research Article
Authors: Yuan, Zhizhua | Hou, Lijuana | Gao, Zihuanb | Wu, Meiqinc | Fan, Jianpingc; *
Affiliations: [a] School of Business Administration, Northeastern University, Shenyang, Liaoning Province, China | [b] School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, Hubei Province, China | [c] School of Economics and Management, Shanxi University, Taiyuan, Shanxi Province, China
Correspondence: [*] Corresponding author. Jianping Fan, School of Economics and Management, Shanxi University, Taiyuan 030006, Shanxi Province, China. E-mail: fjp@sxu.edu.cn.
Abstract: Single-valued neutrosophic sets can efficiently depict a great deal of imprecise, uncertain and discordant information. Hamy mean operator can consider the interrelationships among multiple integrated arguments and Schweizer-Sklar operations express great flexibility in the process of information aggregation. To give full consideration to these advantages, we merge the Hamy mean operator with the Schweizer-Sklar operations in single-valued neutrosophic environment, proposing a single-valued neutrosophic Schweizer-Sklar Hamy mean operator and a single-valued neutrosophic Schweizer-Sklar weighted Hamy mean operator. Besides, we illustrate some specific cases and attributes of the two operators. Moreover, based on the entropy weight method and the single-valued neutrosophic Schweizer-Sklar weighted Hamy mean operator, this paper presents a single-valued neutrosophic Schweizer-Sklar entropic weighted Hamy mean method to tackle multi-attribute decision making problems. At last, the method and other three existing methods are applied to solve a practical multi-attribute decision making problem, which validates the credibility and validity of the single-valued neutrosophic Schweizer-Sklar entropic weighted Hamy mean method by comparing the differences among them.
Keywords: Single-valued neutrosophic sets, Schweizer-Sklar operations, Hamy mean operator, the entropy weight method, multi-attribute decision making
DOI: 10.3233/JIFS-212818
Journal: Journal of Intelligent & Fuzzy Systems, vol. 43, no. 3, pp. 2833-2851, 2022
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