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Model for Multiple Attribute Decision Making Based on Picture 2-Tuple Linguistic Power Aggregation Operators

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  • Guiwu Wei

    (School of Business, Sichuan Normal University, Chengdu, China)

Abstract

In this article, the authors investigate the multiple attribute decision making problems with picture 2-tuple linguistic information. The utilized power average and power geometric operations used to develop some picture 2-tuple linguistic power aggregation operators: picture 2-tuple linguistic power weighted average (P2TLPWA) operator, picture 2-tuple linguistic power weighted geometric (P2TLPWG) operator, picture 2-tuple linguistic power ordered weighted average (P2TLPOWA) operator, picture 2-tuple linguistic power ordered weighted geometric (P2TLPOWG) operator, picture 2-tuple linguistic power hybrid average (P2TLPHA) operator and picture 2-tuple linguistic power hybrid geometric (P2TLPHG) operator. The prominent characteristic of these proposed operators is studied. This article has utilized these operators to develop some approaches to solve the picture 2-tuple linguistic multiple attribute decision making problems. Finally, a practical example for enterprise resource planning (ERP) system selection is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Suggested Citation

  • Guiwu Wei, 2019. "Model for Multiple Attribute Decision Making Based on Picture 2-Tuple Linguistic Power Aggregation Operators," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 11(1), pages 35-65, January.
    • Handle: RePEc:igg:jdsst0:v:11:y:2019:i:1:p:35-65
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