Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry

Abstract This paper describes a consensus-based approach for dealing with multi-person decision-making problems which incorporate probability hesitant fuzzy preference relations. The procedure begins with establishing expected fuzzy preference relations based on the delivered hesitant fuzzy preferen...

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Main Authors: Nighat Rehman, Rukhshanda Anjum, Fikre Bogale Petros
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-88859-8
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author Nighat Rehman
Rukhshanda Anjum
Fikre Bogale Petros
author_facet Nighat Rehman
Rukhshanda Anjum
Fikre Bogale Petros
author_sort Nighat Rehman
collection DOAJ
description Abstract This paper describes a consensus-based approach for dealing with multi-person decision-making problems which incorporate probability hesitant fuzzy preference relations. The procedure begins with establishing expected fuzzy preference relations based on the delivered hesitant fuzzy preference relations using a probabilistic aggregation approach, providing the platform for the framework to make decisions. Then, a multiplicative transitive closure formula is defined to construct multiplicative consistent expected fuzzy preference relations and symmetrical matrices, ensuring the reliability of the preference relations. Following that, a consistency analysis is undertaken to assess the consistency levels of the information provided by experts, allowing them to be assigned information priority weights while also guaranteeing that their inputs are balanced and reliable. In order to make sure that all pertinent factors are taken into account during the decision-making process, the ultimate priority weights for the experts are determined through the combination of consistency-based weights with any specified priority weights, if applicable. The consensus process eventually decides whether to aggregate the data and choose the optimal option based on the collective inputs. To strengthen the experts’ consensus measure, an enhancement method is provided that detects weak viewpoints in cases of poor consensus and allows for targeted modifications. To highlight the suggested scheme’s practicality and usefulness, a comparison example is provided, with results indicating that the method provides valuable insights into the multi-person decision-making process, making it a potential option for achieving agreement in complicated decision-making settings.
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spelling doaj-art-1eafc8cac5f343269e4072c015cfefc22025-02-09T12:30:50ZengNature PortfolioScientific Reports2045-23222025-02-0115111510.1038/s41598-025-88859-8Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industryNighat Rehman0Rukhshanda Anjum1Fikre Bogale Petros2Department of Mathematics and Statistics, University of LahoreDepartment of Mathematics and Statistics, University of LahoreDepartment of Mathematics, Addis Ababa UniversityAbstract This paper describes a consensus-based approach for dealing with multi-person decision-making problems which incorporate probability hesitant fuzzy preference relations. The procedure begins with establishing expected fuzzy preference relations based on the delivered hesitant fuzzy preference relations using a probabilistic aggregation approach, providing the platform for the framework to make decisions. Then, a multiplicative transitive closure formula is defined to construct multiplicative consistent expected fuzzy preference relations and symmetrical matrices, ensuring the reliability of the preference relations. Following that, a consistency analysis is undertaken to assess the consistency levels of the information provided by experts, allowing them to be assigned information priority weights while also guaranteeing that their inputs are balanced and reliable. In order to make sure that all pertinent factors are taken into account during the decision-making process, the ultimate priority weights for the experts are determined through the combination of consistency-based weights with any specified priority weights, if applicable. The consensus process eventually decides whether to aggregate the data and choose the optimal option based on the collective inputs. To strengthen the experts’ consensus measure, an enhancement method is provided that detects weak viewpoints in cases of poor consensus and allows for targeted modifications. To highlight the suggested scheme’s practicality and usefulness, a comparison example is provided, with results indicating that the method provides valuable insights into the multi-person decision-making process, making it a potential option for achieving agreement in complicated decision-making settings.https://doi.org/10.1038/s41598-025-88859-8
spellingShingle Nighat Rehman
Rukhshanda Anjum
Fikre Bogale Petros
Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
Scientific Reports
title Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
title_full Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
title_fullStr Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
title_full_unstemmed Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
title_short Consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
title_sort consensus based sustainable decision making using probability hesitant fuzzy preference relations with application on risk assessment in food industry
url https://doi.org/10.1038/s41598-025-88859-8
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AT fikrebogalepetros consensusbasedsustainabledecisionmakingusingprobabilityhesitantfuzzypreferencerelationswithapplicationonriskassessmentinfoodindustry