Picture 2-tuple linguistic aggregation operators in multiple attribute decision making
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In this paper, we investigate the multiple attribute decision-making problems with picture 2-tuple linguistic information. Then, we utilize arithmetic and geometric operations to develop several picture 2-tuple linguistic aggregation operators. The prominent characteristic of these proposed operators is studied. Then, we have utilized these operators to develop some approaches to solving 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.
KeywordsMultiple attribute decision making The 2-tuple linguistic model Picture fuzzy set Aggregation operators Enterprise resource planning (ERP) system selection
This publication arises from research funded by the National Natural Science Foundation of China under Grant Nos. 61174149 and 71571128 and the Humanities and Social Sciences Foundation of Ministry of Education of the People’s Republic of China (Nos. 16XJA630005, 16YJCZH126) and the construction plan of scientific research innovation team for colleges and universities in Sichuan Province (15TD0004).
Compliance with ethical standards
Conflicts of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
- Chiclana F, Herrera F, Herrera-Viedma E (2000) The ordered weighted geometric operator: Properties and application. In: Proceedings of 8th international conference on information processing and management of uncertainty in knowledge-based systems, Madrid, 2000. pp 985–991Google Scholar
- Cuong B (2013) Picture fuzzy sets-first results. part 1. In: Seminar neuro-fuzzy systems with applications, Institute of Mathematics, HanoiGoogle Scholar
- Merigó JM (2008) New extensions to the OWA operators and their application in decision making. Ph.D. thesis (in Spanish), Department of Business Administration, University of Barcelona, SpainGoogle Scholar
- Merigó JM (2009a) Probabilistic decision making with the OWA operator and its application in investment management. In: Proceedings of the IFSA-EUSFLAT international conference, Lisbon, Portugal, p. 1364–1369Google Scholar
- Merigó JM (2009b) The probabilistic weighted average operator and its application in decision making. In: Lasker GE, Hruza P (eds) Operations systems research & security of information. The international Institute for advanced studies in systems and cybernetics, Baden-Baden, Germany, pp 55–58Google Scholar
- Morente-Molinera JA, Mezei J, Carlsson C, Herrera-Viedma E (2016) Improving supervised learning classification methods using multi-granular linguistic modelling and fuzzy entropy. IEEE transition on fuzzy systems (in press)Google Scholar
- Ngan SC (2011) Decision making with extended fuzzy linguistic computing, with applications to new product development and survey analysis. Expert Syst Appl 38:14052–14059Google Scholar
- Singh P (2014) Correlation coefficients for picture fuzzy sets. J Intell Fuzzy Syst 27:2857–2868Google Scholar
- Thong PH, Son LH (2015) A new approach to multi-variables fuzzy forecasting using picture fuzzy clustering and picture fuzzy rules interpolation method. In: 6th international conference on knowledge and systems engineering, Hanoi, Vietnam, pp. 679–690Google Scholar
- Ye J (2009a) Multicriteria fuzzy decision-making method based on the intuitionistic fuzzy cross-entropy. In: Tang YC, Lawry J, Huynh VN (eds.), Proceedings in international conference on intelligent human–machine systems and cybernetics, 1, IEEE Computer Society, pp. 59–61Google Scholar