Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions

This paper introduces and investigates ranked hesitant fuzzy sets, a novel extension of hesitant fuzzy sets that is less demanding than both probabilistic and proportional hesitant fuzzy sets. This new extension incorporates hierarchical knowledge about the various evaluations submitted for each alt...

Descripción completa

Detalles Bibliográficos
Autor: Alcantud, José Carlos R.
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2022
País:España
Institución:Universidad de Salamanca (USAL)
Repositorio:GREDOS. Repositorio Institucional de la Universidad de Salamanca
OAI Identifier:oai:gredos.usal.es:10366/154210
Acceso en línea:http://hdl.handle.net/10366/154210
Access Level:acceso abierto
Palabra clave:Hesitant fuzzy set
Aggregation operator
Score
Decision making
Ranking
1102.08 Lógica Matemática
id ES_1f0fbfbb3e3ed98fdf1b8ddf41466d99
oai_identifier_str oai:gredos.usal.es:10366/154210
network_acronym_str ES
network_name_str España
repository_id_str
spelling Ranked hesitant fuzzy sets for multi-criteria multi-agent decisionsAlcantud, José Carlos R.Hesitant fuzzy setAggregation operatorScoreDecision makingRanking1102.08 Lógica MatemáticaThis paper introduces and investigates ranked hesitant fuzzy sets, a novel extension of hesitant fuzzy sets that is less demanding than both probabilistic and proportional hesitant fuzzy sets. This new extension incorporates hierarchical knowledge about the various evaluations submitted for each alternative. These evaluations are ranked (for example by their plausibility, acceptability, or credibility), but their position does not necessarily derive from supplementary numerical information (as in probabilistic and proportional hesitant fuzzy sets). In particular, strictly ranked hesitant fuzzy sets arise when no ties exist, i.e., when for any fixed alternative, each submitted evaluation is either strictly more plausible or strictly less plausible than any other submitted evaluation. A detailed comparison with similar models from the literature is performed. Then in order to produce a natural strategy for multi-criteria multi-agent decisions with ranked hesitant fuzzy sets, canonical representations, scores and aggregation operators are designed in the framework of ranked hesitant fuzzy sets. In order to help implementation of this model, Mathematica code is provided for the computation of both scores and aggregators. The decision-making technique that is prescribed is tested with a comparative analysis with four methodologies based on probabilistic hesitant fuzzy information. A conclusion of this numerical exercise is that this methodology is reliable, applicable and robust. All these evidences show that ranked hesitant fuzzy sets are an intuitive extension of the hesitant fuzzy set model designed by V. Torra, that can be implemented in practice with the aid of computationally assisted algorithms.Publicación en abierto financiada por la Universidad de Salamanca como participante en el Acuerdo Transformativo CRUE-CSIC con Elsevier, 2021-2024202420242022info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionhttp://hdl.handle.net/10366/154210reponame:GREDOS. Repositorio Institucional de la Universidad de Salamancainstname:Universidad de Salamanca (USAL)InglésCLU-2019-03Attribution-NonCommercial-NoDerivatives 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:gredos.usal.es:10366/1542102026-06-07T06:28:51Z
dc.title.none.fl_str_mv Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
title Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
spellingShingle Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
Alcantud, José Carlos R.
Hesitant fuzzy set
Aggregation operator
Score
Decision making
Ranking
1102.08 Lógica Matemática
title_short Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
title_full Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
title_fullStr Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
title_full_unstemmed Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
title_sort Ranked hesitant fuzzy sets for multi-criteria multi-agent decisions
dc.creator.none.fl_str_mv Alcantud, José Carlos R.
author Alcantud, José Carlos R.
author_facet Alcantud, José Carlos R.
author_role author
dc.subject.none.fl_str_mv Hesitant fuzzy set
Aggregation operator
Score
Decision making
Ranking
1102.08 Lógica Matemática
topic Hesitant fuzzy set
Aggregation operator
Score
Decision making
Ranking
1102.08 Lógica Matemática
description This paper introduces and investigates ranked hesitant fuzzy sets, a novel extension of hesitant fuzzy sets that is less demanding than both probabilistic and proportional hesitant fuzzy sets. This new extension incorporates hierarchical knowledge about the various evaluations submitted for each alternative. These evaluations are ranked (for example by their plausibility, acceptability, or credibility), but their position does not necessarily derive from supplementary numerical information (as in probabilistic and proportional hesitant fuzzy sets). In particular, strictly ranked hesitant fuzzy sets arise when no ties exist, i.e., when for any fixed alternative, each submitted evaluation is either strictly more plausible or strictly less plausible than any other submitted evaluation. A detailed comparison with similar models from the literature is performed. Then in order to produce a natural strategy for multi-criteria multi-agent decisions with ranked hesitant fuzzy sets, canonical representations, scores and aggregation operators are designed in the framework of ranked hesitant fuzzy sets. In order to help implementation of this model, Mathematica code is provided for the computation of both scores and aggregators. The decision-making technique that is prescribed is tested with a comparative analysis with four methodologies based on probabilistic hesitant fuzzy information. A conclusion of this numerical exercise is that this methodology is reliable, applicable and robust. All these evidences show that ranked hesitant fuzzy sets are an intuitive extension of the hesitant fuzzy set model designed by V. Torra, that can be implemented in practice with the aid of computationally assisted algorithms.
publishDate 2022
dc.date.none.fl_str_mv 2022
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10366/154210
url http://hdl.handle.net/10366/154210
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv CLU-2019-03
dc.rights.none.fl_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Attribution-NonCommercial-NoDerivatives 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:GREDOS. Repositorio Institucional de la Universidad de Salamanca
instname:Universidad de Salamanca (USAL)
instname_str Universidad de Salamanca (USAL)
reponame_str GREDOS. Repositorio Institucional de la Universidad de Salamanca
collection GREDOS. Repositorio Institucional de la Universidad de Salamanca
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869404378214957056
score 15,300719

Similares en LA Referencia