A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation

Hyonil Oh; Jongjin Un; Jongtae Kang; Cholho Ri

doi:doi:10.11648/j.ajist.20220604.12

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A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation

Hyonil Oh, Jongjin Un, Jongtae Kang, Cholho Ri

Published in American Journal of Information Science and Technology (Volume 6, Issue 4)

Received: 1 November 2022 Accepted: 8 December 2022 Published: 27 December 2022

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Abstract

In this paper, we propose a method that can improve a multiplicative inconsistency by revising the potential inconsistent elements of an intuitionistic fuzzy preference relation (IFPR) without constructing a multiplicative consistent IFPR. After converting the given IFPR into a positive reciprocal matrix based on multiplicative consistency, the necessary and sufficient conditions for the IFPR to be multiplicative consistent or inconsistent put forward. A symmetric deviation matrix that can take accurate measurement of consistency bias of every element in an IFPR is constructed. Which of elements in the IFPR corresponding to the largest bias in the deviation matrix are really inconsistent, is verified by a bias verifying vector and a new method of eliminating alternatives, and are uniquely determined by using the fact that all the determinacy degrees of the IFPR remain constant in the revising process. The proposed method can preserve most information of the original IFPR as well as need a few operations in comparison with previous methods because they require to calculate underlying priority weights of alternatives based on a model. Meanwhile an associated example is offered to show the correctness and efficiency of the proposed method.

Published in	American Journal of Information Science and Technology (Volume 6, Issue 4)
DOI	10.11648/j.ajist.20220604.12
Page(s)	86-97
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

Multiplicative Consistency, Determinacy Degree, Symmetric Deviation Matrix, Bias Verifying Vector, Method of Eliminating Alternatives

References

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APA Style

Hyonil Oh, Jongjin Un, Jongtae Kang, Cholho Ri. (2022). A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. American Journal of Information Science and Technology, 6(4), 86-97. https://doi.org/10.11648/j.ajist.20220604.12

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ACS Style

Hyonil Oh; Jongjin Un; Jongtae Kang; Cholho Ri. A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. Am. J. Inf. Sci. Technol. 2022, 6(4), 86-97. doi: 10.11648/j.ajist.20220604.12

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AMA Style

Hyonil Oh, Jongjin Un, Jongtae Kang, Cholho Ri. A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. Am J Inf Sci Technol. 2022;6(4):86-97. doi: 10.11648/j.ajist.20220604.12

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@article{10.11648/j.ajist.20220604.12,
  author = {Hyonil Oh and Jongjin Un and Jongtae Kang and Cholho Ri},
  title = {A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation},
  journal = {American Journal of Information Science and Technology},
  volume = {6},
  number = {4},
  pages = {86-97},
  doi = {10.11648/j.ajist.20220604.12},
  url = {https://doi.org/10.11648/j.ajist.20220604.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20220604.12},
  abstract = {In this paper, we propose a method that can improve a multiplicative inconsistency by revising the potential inconsistent elements of an intuitionistic fuzzy preference relation (IFPR) without constructing a multiplicative consistent IFPR. After converting the given IFPR into a positive reciprocal matrix based on multiplicative consistency, the necessary and sufficient conditions for the IFPR to be multiplicative consistent or inconsistent put forward. A symmetric deviation matrix that can take accurate measurement of consistency bias of every element in an IFPR is constructed. Which of elements in the IFPR corresponding to the largest bias in the deviation matrix are really inconsistent, is verified by a bias verifying vector and a new method of eliminating alternatives, and are uniquely determined by using the fact that all the determinacy degrees of the IFPR remain constant in the revising process. The proposed method can preserve most information of the original IFPR as well as need a few operations in comparison with previous methods because they require to calculate underlying priority weights of alternatives based on a model. Meanwhile an associated example is offered to show the correctness and efficiency of the proposed method.},
 year = {2022}
}

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TY  - JOUR
T1  - A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation
AU  - Hyonil Oh
AU  - Jongjin Un
AU  - Jongtae Kang
AU  - Cholho Ri
Y1  - 2022/12/27
PY  - 2022
N1  - https://doi.org/10.11648/j.ajist.20220604.12
DO  - 10.11648/j.ajist.20220604.12
T2  - American Journal of Information Science and Technology
JF  - American Journal of Information Science and Technology
JO  - American Journal of Information Science and Technology
SP  - 86
EP  - 97
PB  - Science Publishing Group
SN  - 2640-0588
UR  - https://doi.org/10.11648/j.ajist.20220604.12
AB  - In this paper, we propose a method that can improve a multiplicative inconsistency by revising the potential inconsistent elements of an intuitionistic fuzzy preference relation (IFPR) without constructing a multiplicative consistent IFPR. After converting the given IFPR into a positive reciprocal matrix based on multiplicative consistency, the necessary and sufficient conditions for the IFPR to be multiplicative consistent or inconsistent put forward. A symmetric deviation matrix that can take accurate measurement of consistency bias of every element in an IFPR is constructed. Which of elements in the IFPR corresponding to the largest bias in the deviation matrix are really inconsistent, is verified by a bias verifying vector and a new method of eliminating alternatives, and are uniquely determined by using the fact that all the determinacy degrees of the IFPR remain constant in the revising process. The proposed method can preserve most information of the original IFPR as well as need a few operations in comparison with previous methods because they require to calculate underlying priority weights of alternatives based on a model. Meanwhile an associated example is offered to show the correctness and efficiency of the proposed method.
VL  - 6
IS  - 4
ER  -

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Author Information

Hyonil Oh

Institute of Mathematics, State Academy of Sciences, Pyongyang, DPR Korea
Jongjin Un

Department of Information, University of Education, Pyongsong, DPR Korea
Jongtae Kang

Department of Clinical Medicine, Medical University, Nampo, DPR Korea
Cholho Ri

Institute of Automation, State Academy of Sciences, Pyongyang, DPR Korea

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Plain Text BibTeX RIS

APA Style

Hyonil Oh, Jongjin Un, Jongtae Kang, Cholho Ri. (2022). A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. American Journal of Information Science and Technology, 6(4), 86-97. https://doi.org/10.11648/j.ajist.20220604.12

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ACS Style

Hyonil Oh; Jongjin Un; Jongtae Kang; Cholho Ri. A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. Am. J. Inf. Sci. Technol. 2022, 6(4), 86-97. doi: 10.11648/j.ajist.20220604.12

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AMA Style

Hyonil Oh, Jongjin Un, Jongtae Kang, Cholho Ri. A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation. Am J Inf Sci Technol. 2022;6(4):86-97. doi: 10.11648/j.ajist.20220604.12

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@article{10.11648/j.ajist.20220604.12,
  author = {Hyonil Oh and Jongjin Un and Jongtae Kang and Cholho Ri},
  title = {A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation},
  journal = {American Journal of Information Science and Technology},
  volume = {6},
  number = {4},
  pages = {86-97},
  doi = {10.11648/j.ajist.20220604.12},
  url = {https://doi.org/10.11648/j.ajist.20220604.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajist.20220604.12},
  abstract = {In this paper, we propose a method that can improve a multiplicative inconsistency by revising the potential inconsistent elements of an intuitionistic fuzzy preference relation (IFPR) without constructing a multiplicative consistent IFPR. After converting the given IFPR into a positive reciprocal matrix based on multiplicative consistency, the necessary and sufficient conditions for the IFPR to be multiplicative consistent or inconsistent put forward. A symmetric deviation matrix that can take accurate measurement of consistency bias of every element in an IFPR is constructed. Which of elements in the IFPR corresponding to the largest bias in the deviation matrix are really inconsistent, is verified by a bias verifying vector and a new method of eliminating alternatives, and are uniquely determined by using the fact that all the determinacy degrees of the IFPR remain constant in the revising process. The proposed method can preserve most information of the original IFPR as well as need a few operations in comparison with previous methods because they require to calculate underlying priority weights of alternatives based on a model. Meanwhile an associated example is offered to show the correctness and efficiency of the proposed method.},
 year = {2022}
}

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TY  - JOUR
T1  - A Method for Revising the Potential Inconsistent Elements in an Intuitionistic Fuzzy Preference Relation
AU  - Hyonil Oh
AU  - Jongjin Un
AU  - Jongtae Kang
AU  - Cholho Ri
Y1  - 2022/12/27
PY  - 2022
N1  - https://doi.org/10.11648/j.ajist.20220604.12
DO  - 10.11648/j.ajist.20220604.12
T2  - American Journal of Information Science and Technology
JF  - American Journal of Information Science and Technology
JO  - American Journal of Information Science and Technology
SP  - 86
EP  - 97
PB  - Science Publishing Group
SN  - 2640-0588
UR  - https://doi.org/10.11648/j.ajist.20220604.12
AB  - In this paper, we propose a method that can improve a multiplicative inconsistency by revising the potential inconsistent elements of an intuitionistic fuzzy preference relation (IFPR) without constructing a multiplicative consistent IFPR. After converting the given IFPR into a positive reciprocal matrix based on multiplicative consistency, the necessary and sufficient conditions for the IFPR to be multiplicative consistent or inconsistent put forward. A symmetric deviation matrix that can take accurate measurement of consistency bias of every element in an IFPR is constructed. Which of elements in the IFPR corresponding to the largest bias in the deviation matrix are really inconsistent, is verified by a bias verifying vector and a new method of eliminating alternatives, and are uniquely determined by using the fact that all the determinacy degrees of the IFPR remain constant in the revising process. The proposed method can preserve most information of the original IFPR as well as need a few operations in comparison with previous methods because they require to calculate underlying priority weights of alternatives based on a model. Meanwhile an associated example is offered to show the correctness and efficiency of the proposed method.
VL  - 6
IS  - 4
ER  -

Copy | Download