MABAC under non-linear diophantine fuzzy numbers: A new approach for emergency decision support systems

Sohail Ahmad; Ponam Basharat; Saleem Abdullah; Thongchai Botmart; Anuwat Jirawattanapanit; Sohail Ahmad; Ponam Basharat; Saleem Abdullah; Thongchai Botmart; Anuwat Jirawattanapanit

doi:10.3934/math.2022975

AIMS Mathematics

2022, Volume 7, Issue 10: 17699-17736. doi: 10.3934/math.2022975

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Research article

MABAC under non-linear diophantine fuzzy numbers: A new approach for emergency decision support systems

1.
Department of Mathematics, Minhaj University Lahore, Lahore, Pakistan
2.
Department of Mathematics, Abdul Wali Khan University Mardan, Mardan Khyber Pakhtunkhawa, Pakistan
3.
Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
4.
Department of Mathematics, Faculty of Science, Phuket Rajabhat University, Thepkasattree Road Raddasa, Phuket 83000, Thailand

Received: 15 April 2022 Revised: 08 July 2022 Accepted: 13 July 2022 Published: 02 August 2022
MSC : 03E72, 94D05, 90B50

The Covid-19 emergency condition is a critical issue for emergency decision support systems. Controlling the spread of Covid-19 in emergency circumstances throughout the global is a difficult task, hence the purpose of this research is to develop a non-linear diophantine fuzzy decision making mechanism for preventing and identifying Covid-19. Fundamentally, the article is divided into three sections in order to establish suitable and correct procedures to meet the circumstances of emergency decision-making. Firstly, we present a non-linear diophantine fuzzy set (non-LDFS), which is the generalisation of Pythagorean fuzzy set, q-rung orthopair fuzzy set, and linear diophantine fuzzy set, and explain their critical features. In addition, algebraic norms for non-LDFSs are constructed based on particular operational rules. In the second section, we use non-LDF averaging and geometric operator to aggregate expert judgements. The last section of this study consists of ranking in which MABAC (multi-attributive border approximation area comparison) method is used to handle the Covid-19 emergency circumstance using non-LDF information. Moreover, based on the presented methods, the numerical case-study of Covid-19 condition is presented as an application for emergency decision-making. The results shows the efficiency of our proposed techniques and give precise emergency strategies to resolve the worldwide ambiguity of Covid-19.
- non-linear diophantine fuzzy modal,
- multi-criteria decision making,
- MABAC method,
- emergency decision support systems,
- Covid-19
Citation: Sohail Ahmad, Ponam Basharat, Saleem Abdullah, Thongchai Botmart, Anuwat Jirawattanapanit. MABAC under non-linear diophantine fuzzy numbers: A new approach for emergency decision support systems[J]. AIMS Mathematics, 2022, 7(10): 17699-17736. doi: 10.3934/math.2022975

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Abstract

The Covid-19 emergency condition is a critical issue for emergency decision support systems. Controlling the spread of Covid-19 in emergency circumstances throughout the global is a difficult task, hence the purpose of this research is to develop a non-linear diophantine fuzzy decision making mechanism for preventing and identifying Covid-19. Fundamentally, the article is divided into three sections in order to establish suitable and correct procedures to meet the circumstances of emergency decision-making. Firstly, we present a non-linear diophantine fuzzy set (non-LDFS), which is the generalisation of Pythagorean fuzzy set, q-rung orthopair fuzzy set, and linear diophantine fuzzy set, and explain their critical features. In addition, algebraic norms for non-LDFSs are constructed based on particular operational rules. In the second section, we use non-LDF averaging and geometric operator to aggregate expert judgements. The last section of this study consists of ranking in which MABAC (multi-attributive border approximation area comparison) method is used to handle the Covid-19 emergency circumstance using non-LDF information. Moreover, based on the presented methods, the numerical case-study of Covid-19 condition is presented as an application for emergency decision-making. The results shows the efficiency of our proposed techniques and give precise emergency strategies to resolve the worldwide ambiguity of Covid-19.

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