Volume 55, 2021Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
|Page(s)||S435 - S460|
|Published online||09 February 2021|
Approaches to multiple attribute decision making based on picture 2-tuple linguistic power Hamy mean aggregation operators
School of Business, Sichuan Normal University, Chengdu 610101, P.R. China
2 School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, P.R. China
* Corresponding author: firstname.lastname@example.org
Accepted: 7 November 2019
In this paper, the multiple attribute decision making (MADM) problems are investigated with picture 2-tuple linguistic information. Then, based on Hamy mean (HM) operator and dual Hamy mean (DHM) operator, the power average and power geometric operations are utilized to develop some picture 2-tuple linguistic power Hamy mean aggregation operators: picture 2-tuple linguistic power weighted Hamy mean (P2TLPWHM) operator, picture 2-tuple linguistic power weighted dual Hamy mean (P2TLPWDHM) operator, picture 2-tuple linguistic power ordered weighted Hamy mean (P2TLPOWHM) operator, picture 2-tuple linguistic power ordered weighted dual Hamy mean (P2TLPOWDHM) operator, picture 2-tuple linguistic power hybrid Hamy mean (P2TLPHHM) operator and picture 2-tuple linguistic power hybrid dual Hamy mean (P2TLPHDHM) operator. The prominent characteristic of these proposed operators are studied. Then, these operators are utilized to develop some approaches to solve the picture 2-tuple linguistic multiple attribute decision making problems. Finally, the proposed method is demonstrated through a practical example for enterprise resource planning (ERP) system selection of how the proposed methods help us and is effective in MADM problems.
Key words: Multiple attribute decision making (MADM) / picture 2-tuple linguistic set / power weighted Hamy mean (PWHM) operator / power weighted dual Hamy mean (PWDHM) operator / enterprise resource planning (ERP)
© EDP Sciences, ROADEF, SMAI 2021
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