Khan, Qaisar and Mahmood, Tahir and Ullah, Kifayat (2021) Applications of improved spherical fuzzy Dombi aggregation operators in decision support system. Applications of improved spherical fuzzy Dombi aggregation operators in decision support system. ISSN 1433-7479
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Abstract
Spherical fuzzy sets are an extension of various fuzzy concepts and demonstrate fuzzy opinion using membership, abstinence, non-membership and refusal degrees with relaxed conditions, and it is a better mathematical tool to deal with uncertain and vague information. Recently, Dombi operational laws for spherical fuzzy numbers (SPFNs) are developed for multi-attribute decision-making purpose. In this article, some limitations of the said Dombi operational laws for SPFNs are investigated as the aggregated information that came out using existing aggregation operators deviate from the range. Therefore, in this paper, we aim to present some improved Dombi operational laws for SPFNs. Further, keeping the advantages of the power aggregation operators that it takes into account the relationship of the information being aggregated, we aim to develop the spherical fuzzy Dombi power average operator, the spherical fuzzy Dombi weighted power average operator, spherical fuzzy Dombi power geometric operator, and spherical fuzzy Dombi weighted power geometric operator and their desirable properties are discussed. The main advantage of these developed Dombi power aggregation operators is that they eliminate the effect of awkward data and are more flexible due to general parameters involved in the aggregation process. Moreover, based on these Dombi power aggregation operators, a novel multi-attribute group decision-making approach is instituted followed by a numerical example to show the practicality and effectiveness of the proposed approach and comparison with the existing approaches is also given.
Item Type: | Article |
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Subjects: | Q Science > Q Science (General) Q Science > QA Mathematics |
Divisions: | Faculty of Engineering and Applied Sciences (FEAS) > Department of Basic Sciences Lahore |
Depositing User: | Dr. Kifayat Ullah |
Date Deposited: | 28 May 2021 07:19 |
Last Modified: | 28 May 2021 07:19 |
URI: | http://research.riphah.edu.pk/id/eprint/1477 |
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