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Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers for multiple attribute group decision making


Autoři: Yanru Zhong aff001;  Hong Gao aff001;  Xiuyan Guo aff001;  Yuchu Qin aff002;  Meifa Huang aff003;  Xiaonan Luo aff001
Působiště autorů: Guangxi Key Laboratory of Intelligent Processing of Computer Images and Graphics, Guilin University of Electronic Technology, Guilin, PR China aff001;  School of Computing and Engineering, University of Huddersfield, Huddersfield, United Kingdom aff002;  School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin, PR China aff003
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0222007

Souhrn

In this paper, a set of Dombi power partitioned Heronian mean operators of q-rung orthopair fuzzy numbers (qROFNs) are presented, and a multiple attribute group decision making (MAGDM) method based on these operators is proposed. First, the operational rules of qROFNs based on the Dombi t-conorm and t-norm are introduced. A q-rung orthopair fuzzy Dombi partitioned Heronian mean (qROFDPHM) operator and its weighted form are then established in accordance with these rules. To reduce the negative effect of unreasonable attribute values on the aggregation results of these operators, a q-rung orthopair fuzzy Dombi power partitioned Heronian mean operator and its weighted form are constructed by combining qROFDPHM operator with the power average operator. A method to solve MAGDM problems based on qROFNs and the constructed operators is designed. Finally, a practical example is described, and experiments and comparisons are performed to demonstrate the feasibility and effectiveness of the proposed method. The demonstration results show that the method is feasible, effective, and flexible; has satisfying expressiveness; and can consider all the interrelationships among different attributes and reduce the negative influence of biased attribute values.

Klíčová slova:

Calculus – Data processing – Decision making – Distance measurement – Environmental impacts – Pattern recognition receptors – Real numbers


Zdroje

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