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Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis
To objectively evaluate the influence of hesitant fuzziness on the ranking of alternatives in multi-attribute decision making with hesitant fuzzy or probabilistic hesitant fuzzy information, the binary connection number of set pair analysis is applied to hesitant fuzzy multi-attribute decision makin...
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/PMC8488077/ https://www.ncbi.nlm.nih.gov/pubmed/34629955 http://dx.doi.org/10.1007/s00500-021-06215-0 |
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author | Shen, Qing Lou, Jungang Liu, Yong Jiang, Yunliang |
author_facet | Shen, Qing Lou, Jungang Liu, Yong Jiang, Yunliang |
author_sort | Shen, Qing |
collection | PubMed |
description | To objectively evaluate the influence of hesitant fuzziness on the ranking of alternatives in multi-attribute decision making with hesitant fuzzy or probabilistic hesitant fuzzy information, the binary connection number of set pair analysis is applied to hesitant fuzzy multi-attribute decision making. The hesitant or probabilistic hesitant fuzzy set is transformed to the binary connection number. A hesitant fuzzy multi-attribute decision making model based on binary connection number is then established. Binary connection number theory is utilized to obtain the hesitant fuzzy center and decision-making suggestions about the alternative ranking under different hesitant fuzzy conditions. Experimental examples show that the hesitant fuzzy multi-attribute decision making model based on binary connection number has a certain versatility. It can determine the optimal scheme under the influence of hesitant fuzziness on the alternative ranking and contains the results of the same hesitant fuzzy decision-making problem using other methods, which helps in targeted decision making according to different hesitant fuzzy conditions. |
format | Online Article Text |
id | pubmed-8488077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-84880772021-10-04 Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis Shen, Qing Lou, Jungang Liu, Yong Jiang, Yunliang Soft comput Soft Computing in Decision Making and in Modeling in Economics To objectively evaluate the influence of hesitant fuzziness on the ranking of alternatives in multi-attribute decision making with hesitant fuzzy or probabilistic hesitant fuzzy information, the binary connection number of set pair analysis is applied to hesitant fuzzy multi-attribute decision making. The hesitant or probabilistic hesitant fuzzy set is transformed to the binary connection number. A hesitant fuzzy multi-attribute decision making model based on binary connection number is then established. Binary connection number theory is utilized to obtain the hesitant fuzzy center and decision-making suggestions about the alternative ranking under different hesitant fuzzy conditions. Experimental examples show that the hesitant fuzzy multi-attribute decision making model based on binary connection number has a certain versatility. It can determine the optimal scheme under the influence of hesitant fuzziness on the alternative ranking and contains the results of the same hesitant fuzzy decision-making problem using other methods, which helps in targeted decision making according to different hesitant fuzzy conditions. Springer Berlin Heidelberg 2021-10-04 2021 /pmc/articles/PMC8488077/ /pubmed/34629955 http://dx.doi.org/10.1007/s00500-021-06215-0 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 | Soft Computing in Decision Making and in Modeling in Economics Shen, Qing Lou, Jungang Liu, Yong Jiang, Yunliang Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title | Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title_full | Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title_fullStr | Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title_full_unstemmed | Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title_short | Hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
title_sort | hesitant fuzzy multi-attribute decision making based on binary connection number of set pair analysis |
topic | Soft Computing in Decision Making and in Modeling in Economics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8488077/ https://www.ncbi.nlm.nih.gov/pubmed/34629955 http://dx.doi.org/10.1007/s00500-021-06215-0 |
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