Generalization and ranking of fuzzy numbers by relative preference relation

Kavitha Koppula; Babushri Srinivas Kedukodi; Syam Prasad Kuncham

doi:10.1007/s00500-021-06616-1

Generalization and ranking of fuzzy numbers by relative preference relation

Kavitha Koppula
, Babushri Srinivas Kedukodi^*
, Syam Prasad Kuncham

^*Corresponding author for this work

Manipal Institute of Technology, Manipal

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

We define 2 n+ 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank 2 n+ 1 and 2n fuzzy numbers. When the data is representable in terms of 2 n+ 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.

Original language	English
Pages (from-to)	1101-1122
Number of pages	22
Journal	Soft Computing
Volume	26
Issue number	3
DOIs	https://doi.org/10.1007/s00500-021-06616-1
Publication status	Published - 02-2022

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Software
Geometry and Topology

Access to Document

10.1007/s00500-021-06616-1

Cite this

@article{438ad1ba072342198c6c15f15f0f03b0,

title = "Generalization and ranking of fuzzy numbers by relative preference relation",

abstract = "We define 2 n+ 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank 2 n+ 1 and 2n fuzzy numbers. When the data is representable in terms of 2 n+ 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.",

author = "Kavitha Koppula and Kedukodi, \{Babushri Srinivas\} and Kuncham, \{Syam Prasad\}",

note = "Funding Information: The authors thank the anonymous reviewers for their valuable comments and suggestions. All authors acknowledge the support and encouragement of Manipal Institute of Technology, Manipal Academy of Higher Education (MAHE), Manipal. Publisher Copyright: {\textcopyright} 2021, The Author(s).",

year = "2022",

month = feb,

doi = "10.1007/s00500-021-06616-1",

language = "English",

volume = "26",

pages = "1101--1122",

journal = "Soft Computing",

issn = "1432-7643",

publisher = "Springer Science and Business Media Deutschland GmbH",

number = "3",

}

TY - JOUR

T1 - Generalization and ranking of fuzzy numbers by relative preference relation

AU - Koppula, Kavitha

AU - Kedukodi, Babushri Srinivas

AU - Kuncham, Syam Prasad

N1 - Funding Information: The authors thank the anonymous reviewers for their valuable comments and suggestions. All authors acknowledge the support and encouragement of Manipal Institute of Technology, Manipal Academy of Higher Education (MAHE), Manipal. Publisher Copyright: © 2021, The Author(s).

PY - 2022/2

Y1 - 2022/2

N2 - We define 2 n+ 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank 2 n+ 1 and 2n fuzzy numbers. When the data is representable in terms of 2 n+ 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.

AB - We define 2 n+ 1 and 2n fuzzy numbers, which generalize triangular and trapezoidal fuzzy numbers, respectively. Then, we extend the fuzzy preference relation and relative preference relation to rank 2 n+ 1 and 2n fuzzy numbers. When the data is representable in terms of 2 n+ 1 fuzzy number, we generalize the FMCDM (fuzzy multi-criteria decision making) model constructed with TOPSIS and relative preference relation. Lastly, we give an example from telecommunications to present the proposed FMCDM model and validate the results obtained.

UR - https://www.scopus.com/pages/publications/85121832237

UR - https://www.scopus.com/pages/publications/85121832237#tab=citedBy

U2 - 10.1007/s00500-021-06616-1

DO - 10.1007/s00500-021-06616-1

M3 - Article

AN - SCOPUS:85121832237

SN - 1432-7643

VL - 26

SP - 1101

EP - 1122

JO - Soft Computing

JF - Soft Computing

IS - 3

ER -

Generalization and ranking of fuzzy numbers by relative preference relation

Abstract

All Science Journal Classification (ASJC) codes

Access to Document

Other files and links

Fingerprint

Cite this