Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets

N. Agell; Mónica Sánchez; Francesc Prats; Francisco Javier Ruiz

doi:10.3233/978-1-61499-578-4-71

Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets

N. Agell, Mónica Sánchez, Francesc Prats, Francisco Javier Ruiz

Esade Business School

Research output: Book chapter › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is introduced based on the properties of the lattice. This metric structure allows distances between decision makers to be computed. A centroid or group representative is defined in group decision-making processes where decision makers are assessing different alternatives by means of hesitant fuzzy linguistic term sets.

Original language	English
Title of host publication	Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence
Editors	Dionis Boixader, Francisco Grimaldo, Eva Armengol
Publisher	IOS Press
Pages	71-79
Number of pages	9
ISBN (Electronic)	9781614995777
DOIs	https://doi.org/10.3233/978-1-61499-578-4-71
Publication status	Published - 2015
Event	18th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2015 - Valencia, Spain Duration: 21 Oct 2015 → 23 Oct 2015

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	277
ISSN (Print)	0922-6389

Conference

Conference	18th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2015
Country/Territory	Spain
City	Valencia
Period	21/10/15 → 23/10/15

Keywords

Decision support
Knowledge Management
Uncertainty and fuzzy reasoning

Access to Document

10.3233/978-1-61499-578-4-71

Cite this

Agell, N., Sánchez, M., Prats, F., & Ruiz, F. J. (2015). Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets. In D. Boixader, F. Grimaldo, & E. Armengol (Eds.), Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence (pp. 71-79). (Frontiers in Artificial Intelligence and Applications; Vol. 277). IOS Press. https://doi.org/10.3233/978-1-61499-578-4-71

Agell, N. ; Sánchez, Mónica ; Prats, Francesc et al. / Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets. Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence. editor / Dionis Boixader ; Francisco Grimaldo ; Eva Armengol. IOS Press, 2015. pp. 71-79 (Frontiers in Artificial Intelligence and Applications).

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abstract = "Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is introduced based on the properties of the lattice. This metric structure allows distances between decision makers to be computed. A centroid or group representative is defined in group decision-making processes where decision makers are assessing different alternatives by means of hesitant fuzzy linguistic term sets.",

keywords = "Decision support, Knowledge Management, Uncertainty and fuzzy reasoning",

author = "N. Agell and M{\'o}nica S{\'a}nchez and Francesc Prats and Ruiz, {Francisco Javier}",

note = "Publisher Copyright: {\textcopyright} 2015 The authors and IOS Press. All rights reserved..; 18th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2015 ; Conference date: 21-10-2015 Through 23-10-2015",

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language = "English",

series = "Frontiers in Artificial Intelligence and Applications",

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Agell, N, Sánchez, M, Prats, F & Ruiz, FJ 2015, Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets. in D Boixader, F Grimaldo & E Armengol (eds), Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence. Frontiers in Artificial Intelligence and Applications, vol. 277, IOS Press, pp. 71-79, 18th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2015, Valencia, Spain, 21/10/15. https://doi.org/10.3233/978-1-61499-578-4-71

Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets. / Agell, N.; Sánchez, Mónica; Prats, Francesc et al.
Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence. ed. / Dionis Boixader; Francisco Grimaldo; Eva Armengol. IOS Press, 2015. p. 71-79 (Frontiers in Artificial Intelligence and Applications; Vol. 277).

Research output: Book chapter › Conference contribution › peer-review

TY - GEN

T1 - Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets

AU - Agell, N.

AU - Sánchez, Mónica

AU - Prats, Francesc

AU - Ruiz, Francisco Javier

PY - 2015

Y1 - 2015

N2 - Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is introduced based on the properties of the lattice. This metric structure allows distances between decision makers to be computed. A centroid or group representative is defined in group decision-making processes where decision makers are assessing different alternatives by means of hesitant fuzzy linguistic term sets.

AB - Given a finite totally ordered set of linguistic terms, the operations intersection and connected union provide a lattice structure to the set of hesitant fuzzy linguistic term sets. In this framework, hesitant fuzzy linguistic descriptions of a given set of alternatives are considered. A distance between hesitant fuzzy linguistic descriptions is introduced based on the properties of the lattice. This metric structure allows distances between decision makers to be computed. A centroid or group representative is defined in group decision-making processes where decision makers are assessing different alternatives by means of hesitant fuzzy linguistic term sets.

KW - Decision support

KW - Knowledge Management

KW - Uncertainty and fuzzy reasoning

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U2 - 10.3233/978-1-61499-578-4-71

DO - 10.3233/978-1-61499-578-4-71

M3 - Conference contribution

AN - SCOPUS:84948823507

T3 - Frontiers in Artificial Intelligence and Applications

SP - 71

EP - 79

BT - Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence

A2 - Boixader, Dionis

A2 - Grimaldo, Francisco

A2 - Armengol, Eva

PB - IOS Press

T2 - 18th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2015

Y2 - 21 October 2015 through 23 October 2015

ER -

Agell N, Sánchez M, Prats F, Ruiz FJ. Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets. In Boixader D, Grimaldo F, Armengol E, editors, Artificial Intelligence Research and Development - Proceedings of the 18th International Conference of the Catalan Association for Artificial Intelligence. IOS Press. 2015. p. 71-79. (Frontiers in Artificial Intelligence and Applications). doi: 10.3233/978-1-61499-578-4-71

Computing Distances between Decision Makers Using Hesitant Fuzzy Linguistic Term Sets

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