LR-Type Spherical Fuzzy Numbers and Their Usage in MCDM Problems

Cengiz Kahraman*, Sezi Cevik Onar, Basar Öztaysi

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Spherical fuzzy sets (SFS) are recent extension of ordinary fuzzy sets, which are composed of three parameters whose squared sum is at most one. SFS are defined by discrete values of these three parameters and provide a larger assignment volume than picture fuzzy sets. We propose a non-linear continuous membership, non-membership, and/or hesitancy function for spherical fuzzy sets based on LR-type nonlinear fuzzy numbers. We illustrate their usage in multiple criteria supplier selection problems. The paper is concluded by limitations and suggestions for further research.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
EditorsCengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
PublisherSpringer Science and Business Media Deutschland GmbH
Pages275-283
Number of pages9
ISBN (Print)9783031397738
DOIs
Publication statusPublished - 2023
EventIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey
Duration: 22 Aug 202324 Aug 2023

Publication series

NameLecture Notes in Networks and Systems
Volume758 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Country/TerritoryTurkey
CityIstanbul
Period22/08/2324/08/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • LR-fuzzy numbers
  • MCDM
  • spherical fuzzy sets
  • supplier selection

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