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Article type: Research Article
Authors: Xu, Xin-Ruia | Wei, Gui-Wub; *
Affiliations: [a] School of Civil Engineering, Chongqing University of Arts and Sciences, Yongchuan 402160, Chongqing, China | [b] School of Business, Sichuan Normal University, Chengdu 610101, Sichuan, China
Correspondence: [*] Corresponding author: Gui-Wu Wei, School of Business, Sichuan Normal University, Chengdu 610101, Sichuan, China. Tel./ Fax: +86 028 84480719; E-mail: [email protected].
Abstract: In this paper, we investigate the multiple attribute decision making problems based on the aggregation operators with dual hesitant bipolar fuzzy information. Firstly, we propose the concept of the dual hesitant bipolar fuzzy set and fundamental operational laws of dual hesitant bipolar fuzzy numbers. Then, motivated by the ideal of arithmetic and geometric operation, we have developed some aggregation operators for aggregating dual hesitant bipolar fuzzy information: dual hesitant bipolar fuzzy weighted average (DHBFWA) operator, dual hesitant bipolar fuzzy weighted geometric (DHBFWG) operator, dual hesitant bipolar fuzzy ordered weighted average (DHBFOWA) operator, dual hesitant bipolar fuzzy ordered weighted geometric (DHBFOWG) operator, dual hesitant bipolar fuzzy hybrid average (DHBFHA) operator and dual hesitant bipolar fuzzy hybrid geometric (DHBFHG) operator. Then, we have utilized these operators to develop some approaches to solve the dual hesitant bipolar fuzzy multiple attribute decision making problems. Finally, an illustrative example for evaluating the constructional engineering software quality is then analyzed to illustrate the relevance and effectiveness of the proposed methodology.
Keywords: Multiple attribute decision making (MADM), bipolar fuzzy set, dual hesitant bipolar fuzzy set, dual hesitant bipolar fuzzy hybrid average (DHBFHA) operator, dual hesitant bipolar fuzzy hybrid geometric (DHBFHG) operator, software quality, constructional engineering
DOI: 10.3233/KES-170360
Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 21, no. 3, pp. 155-164, 2017
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