Extension of VIKOR Method Using Circular Intuitionistic Fuzzy Sets

Cengiz Kahraman*, Irem Otay

*Corresponding author for this work

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

20 Citations (Scopus)


VIKOR method is used to solve a variety of MCDM problems including a variety of criteria that can be conflicting and noncommensurable. This method is based on the distances of alternatives to positive and negative ideal solutions, and provides compromising solutions. Decision makers generally prefer to evaluate the alternatives with respect to the criteria by using linguistic terms rather than assigning exact numerical values. The fuzzy set theory captures the uncertainty and subjectivity in these linguistic terms successfully. Many classical MCDM methods have been extended to their fuzzy versions by using the fuzzy set theory for handling this uncertainty. VIKOR method has been extended by using several fuzzy set extensions such as intuitionistic fuzzy VIKOR, hesitant fuzzy VIKOR, Pythagorean fuzzy VIKOR, picture fuzzy VIKOR, and spherical fuzzy VIKOR methods. Circular intuitionistic fuzzy sets (C-IFS) introduced as an extension of intuitionistic fuzzy sets, enables decision makers to define membership and the non-membership degrees as circular membership functions. In this paper, we develop C-IFS VIKOR method and apply it to a waste disposal location selection problem.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation - Proceedings of the INFUS 2021 Conference
EditorsCengiz Kahraman, Selcuk Cebi, Sezi Cevik Onar, Basar Oztaysi, A. Cagri Tolga, Irem Ucal Sari
PublisherSpringer Science and Business Media Deutschland GmbH
Number of pages10
ISBN (Print)9783030855765
Publication statusPublished - 2022
EventInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021 - Istanbul, Turkey
Duration: 24 Aug 202126 Aug 2021

Publication series

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


ConferenceInternational Conference on Intelligent and Fuzzy Systems, INFUS 2021

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.


  • Circular intuitionistic fuzzy sets
  • Fuzzy MCDM
  • Fuzzy set extensions


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