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Multi-criteria group decision making based on Archimedean power partitioned Muirhead mean operators of q-rung orthopair fuzzy numbers

Author

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  • Yuchu Qin
  • Qunfen Qi
  • Paul J Scott
  • Xiangqian Jiang

Abstract

Two critical tasks in multi-criteria group decision making (MCGDM) are to describe criterion values and to aggregate the described information to generate a ranking of alternatives. A flexible and superior tool for the first task is q-rung orthopair fuzzy number (qROFN) and an effective tool for the second task is aggregation operator. So far, nearly thirty different aggregation operators of qROFNs have been presented. Each operator has its distinctive characteristics and can work well for specific purpose. However, there is not yet an operator which can provide desirable generality and flexibility in aggregating criterion values, dealing with the heterogeneous interrelationships among criteria, and reducing the influence of extreme criterion values. To provide such an aggregation operator, Muirhead mean operator, power average operator, partitioned average operator, and Archimedean T-norm and T-conorm operations are concurrently introduced into q-rung orthopair fuzzy sets, and an Archimedean power partitioned Muirhead mean operator of qROFNs and its weighted form are presented and a MCGDM method based on the weighted operator is proposed in this paper. The generalised expressions of the two operators are firstly defined. Their properties are explored and proved and their specific expressions are constructed. On the basis of the specific expressions, a method for solving the MCGDM problems based on qROFNs is then designed. Finally, the feasibility and effectiveness of the method is demonstrated via a numerical example, a set of experiments, and qualitative and quantitative comparisons.

Suggested Citation

  • Yuchu Qin & Qunfen Qi & Paul J Scott & Xiangqian Jiang, 2019. "Multi-criteria group decision making based on Archimedean power partitioned Muirhead mean operators of q-rung orthopair fuzzy numbers," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-35, September.
  • Handle: RePEc:plo:pone00:0221759
    DOI: 10.1371/journal.pone.0221759
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    References listed on IDEAS

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    1. Harish Garg & Rishu Arora, 2018. "Bonferroni mean aggregation operators under intuitionistic fuzzy soft set environment and their applications to decision-making," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(11), pages 1711-1724, November.
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