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Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers
Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have sho...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211316/ https://www.ncbi.nlm.nih.gov/pubmed/34178177 http://dx.doi.org/10.1007/s12652-021-03347-x |
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author | Dutta, Palash Borah, Gourangajit |
author_facet | Dutta, Palash Borah, Gourangajit |
author_sort | Dutta, Palash |
collection | PubMed |
description | Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have showcased their lack of efficiency and hence eventually it has paved the ways for the development of Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision makers can model most of the real-life phenomena by fuzzy information-based preferences. The availability of a wide literature on similarity measure (SM) emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct accurate and precise decision making in FMCDM problems. Despite having few advantages, most of the existing approaches possessed a certain degree of counter intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately overcome the impediments associated with the earlier existing approaches. Moreover, a meticulous comparative study with the existing approaches is also presented. This paper provides us with an improved method to obtain the similarity values between GTrFNs and the proposed SM consists of calculating the prominent features of fuzzy numbers such as expected value and variance. We use fourteen different sets of GTrFNs, to compare the fruition of the present approach with the existing SM approaches. Furthermore, to show the utility and applicability of our proposed measure, we illustrate few practical scenarios such as the launching of an electronic gadget by a company, a problem of medical diagnosis and finally, a proper anti-virus mask selection in light of the recent COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned FMCDM problems, are analytically correct and they depict the efficiency and novelty of the present article. |
format | Online Article Text |
id | pubmed-8211316 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-82113162021-06-21 Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers Dutta, Palash Borah, Gourangajit J Ambient Intell Humaniz Comput Original Research Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have showcased their lack of efficiency and hence eventually it has paved the ways for the development of Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision makers can model most of the real-life phenomena by fuzzy information-based preferences. The availability of a wide literature on similarity measure (SM) emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct accurate and precise decision making in FMCDM problems. Despite having few advantages, most of the existing approaches possessed a certain degree of counter intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately overcome the impediments associated with the earlier existing approaches. Moreover, a meticulous comparative study with the existing approaches is also presented. This paper provides us with an improved method to obtain the similarity values between GTrFNs and the proposed SM consists of calculating the prominent features of fuzzy numbers such as expected value and variance. We use fourteen different sets of GTrFNs, to compare the fruition of the present approach with the existing SM approaches. Furthermore, to show the utility and applicability of our proposed measure, we illustrate few practical scenarios such as the launching of an electronic gadget by a company, a problem of medical diagnosis and finally, a proper anti-virus mask selection in light of the recent COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned FMCDM problems, are analytically correct and they depict the efficiency and novelty of the present article. Springer Berlin Heidelberg 2021-06-17 2023 /pmc/articles/PMC8211316/ /pubmed/34178177 http://dx.doi.org/10.1007/s12652-021-03347-x Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Dutta, Palash Borah, Gourangajit Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title | Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title_full | Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title_fullStr | Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title_full_unstemmed | Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title_short | Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
title_sort | multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8211316/ https://www.ncbi.nlm.nih.gov/pubmed/34178177 http://dx.doi.org/10.1007/s12652-021-03347-x |
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