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Article type: Research Article
Authors: Zhao, Xiaofei | Li, Qingxiang | Wei, Guiwu
Affiliations: School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan, China | School of Software Engineering, Chongqing University of Arts and Sciences, Yongchuan, China
Note: [] Corresponding author. Guiwu Wei, School of Economics and Management, Chongqing University of Arts and Sciences, Yongchuan 402160, China. Tel./Fax: +86 2349891872; E-mail: [email protected]
Abstract: In this paper, we investigate the linguistic multiple attribute group decision making (MADM) problems in which the attributes and experts are in different priority level. Motivated by the ideal of prioritized aggregation operators (R.R. Yager, Prioritized aggregation operators, International Journal of Approximate Reasoning 48(2008) 263-274.), we develop some prioritized aggregation operators for aggregating linguistic information, and then apply them to develop some models for linguistic multiple attribute group decision making (MAGDM) problems in which the attributes and experts are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords: Multiple attribute group decision making (MAGDM), linguistic information, prioritized aggregation operators, 2-tuple linguistic prioritized weighted average (2TLPWA) operator, 2-tuple linguistic prioritized weighted geometric (2TLPWG) operator, 2-tuple linguistic prioritized weighted harmonic average (2TLPWHA) operator
DOI: 10.3233/IFS-130842
Journal: Journal of Intelligent & Fuzzy Systems, vol. 26, no. 4, pp. 1619-1630, 2014
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