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Emergency decision support modeling under generalized spherical fuzzy Einstein aggregation information

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Abstract

Dominant emergency action should be adopted in the case of an emergency situation. Emergency is interpreted as limited time and information, harmfulness and uncertainty, and decision-makers are often critically bound by uncertainty and risk. This framework implements an emergency decision-making approach to address the emergency situation of COVID-19 in a spherical fuzzy environment. As the spherical fuzzy set (SFS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). Keeping in view the features of the SFSs, the purpose of this paper is to present some robust generalized operating laws in accordance with the Einstein norms. In addition, list of propose aggregation operators using Einstein operational laws under spherical fuzzy environment are developed. Furthermore, we design the algorithm based on the proposed aggregation operators to tackle the uncertainty in emergency decision making problems. Finally, numerical case study of COVID-19 as an emergency decision making is presented to demonstrate the applicability and validity of the proposed technique. Besides, the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique.

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Acknowledgement

This study was supported by Higher Education Commission (HEC), Pakistan under National Research Program for University (NRPU), Project title: Fuzzy Mathematical Modeling for Decision Support Systems and Smart Grid Systems (No. 10701/KPK/NRPU/R&D/HEC/2017).

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Authors and Affiliations

  1. Department of Mathematics and Statistics, Bacha Khan University, Charsadda, 24420, Khyber Pakhtunkhwa, Pakistan

    Shahzaib Ashraf

  2. Department of Mathematics, Abdul Wali Khan University, Mardan, 23200, Khyber Pakhtunkhwa, Pakistan

    Saleem Abdullah

  3. Department of Mathematics and Statistics, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand

    Ronnason Chinram

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  1. Shahzaib Ashraf
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  2. Saleem Abdullah
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  3. Ronnason Chinram
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Correspondence to Shahzaib Ashraf.

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Ashraf, S., Abdullah, S. & Chinram, R. Emergency decision support modeling under generalized spherical fuzzy Einstein aggregation information. J Ambient Intell Human Comput 13, 2091–2117 (2022). https://doi.org/10.1007/s12652-021-03493-2

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