Research article

Spherical fuzzy rough Hamacher aggregation operators and their application in decision making problem

  • Received: 01 January 2023 Revised: 05 March 2023 Accepted: 04 April 2023 Published: 17 May 2023
  • MSC : 03E72, 47S40

  • Aggregation operators are the most effective mathematical tools for aggregating many variables into a single result. The aggregation operators operate to bring together all of the different assessment values offered in a common manner, and they are highly helpful for assessing the options offered in the decision-making process. The spherical fuzzy sets (SFSs) and rough sets are common mathematical tools that are capable of handling incomplete and ambiguous information. We also establish the concepts of spherical fuzzy rough Hamacher averaging and spherical fuzzy rough Hamacher geometric operators. The key characteristics of the suggested operators are thoroughly described. We create an algorithm for a multi-criteria group decision making (MCGDM) problem to cope with the ambiguity and uncertainty. A numerical example of the developed models is shown in the final section. The results show that the specified models are more efficient and advantageous than the other existing approaches when the offered models are contrasted with specific present methods.

    Citation: Muhammad Naeem, Muhammad Qiyas, Lazim Abdullah, Neelam Khan, Salman Khan. Spherical fuzzy rough Hamacher aggregation operators and their application in decision making problem[J]. AIMS Mathematics, 2023, 8(7): 17112-17141. doi: 10.3934/math.2023874

    Related Papers:

  • Aggregation operators are the most effective mathematical tools for aggregating many variables into a single result. The aggregation operators operate to bring together all of the different assessment values offered in a common manner, and they are highly helpful for assessing the options offered in the decision-making process. The spherical fuzzy sets (SFSs) and rough sets are common mathematical tools that are capable of handling incomplete and ambiguous information. We also establish the concepts of spherical fuzzy rough Hamacher averaging and spherical fuzzy rough Hamacher geometric operators. The key characteristics of the suggested operators are thoroughly described. We create an algorithm for a multi-criteria group decision making (MCGDM) problem to cope with the ambiguity and uncertainty. A numerical example of the developed models is shown in the final section. The results show that the specified models are more efficient and advantageous than the other existing approaches when the offered models are contrasted with specific present methods.



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