Yang, Zaoli, Garg, Harish, Peng, Rui, Wu, Shaomin, Huang, Lucheng (2020) Group Decision Algorithm for Aged Healthcare Product Purchase Under q-Rung Picture Normal Fuzzy Environment Using Heronian Mean Operator. International Journal of Computational Intelligence Systems, 13 (1). pp. 1176-1197. ISSN 1875-6891. E-ISSN 1875-6883. (doi:10.2991/ijcis.d.200803.001) (KAR id:84011)
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Official URL: https://dx.doi.org/10.2991/ijcis.d.200803.001 |
Abstract
With the intensification of the aging, the health issue of the elderly is arousing public concern increasingly. Various healthcare products for the elderly are emerging from the market, thus how to select suitable aged healthcare product is critical to the well-being of the elderly. In the literature, nonetheless, a comprehensive and standardized evaluation framework to support healthcare product purchase decision for the aged is currently lacking. This paper proposes a novel group decision-making method to aid the decision-making of aged healthcare product purchase based on q-rung picture normal fuzzy Heronian mean (q-RPtNoFHM) operators. In it, firstly, a new fuzzy variable called the q-rung picture normal fuzzy set (q-RPtNoFS) is defined to reasonably describe different responses to healthcare product evaluation, for which, some definitions including operational laws, a score function, and an accuracy function of q-RPtNoFSs are introduced. Then, two q-RPtNoFHM operators are presented to aggregate group decision information. In addition, some properties of q-RPtNoFHM operators, such as monotonicity, commutativity, and idempotency, are discussed. Finally, an example on antihypertensive drugs purchase is gave to illustrate the practicality of the proposed method, and conduct sensitivity analysis to analyze the effectiveness and flexibility of proposed methods.
Item Type: | Article |
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DOI/Identification number: | 10.2991/ijcis.d.200803.001 |
Uncontrolled keywords: | Aged healthcare product purchase, Group decision-making, q-rung picture normal fuzzy sets, Heronian mean operators |
Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Shaomin Wu |
Date Deposited: | 09 Nov 2020 20:41 UTC |
Last Modified: | 04 Mar 2024 16:13 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/84011 (The current URI for this page, for reference purposes) |
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