A satisfactory consistency judging method of linguistic judgment matrix based on transitive closure

Yunlong Zhang , Fengxia Jin , Jingfei Jiang , Juan LG Guirao , Huatao Chen

Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (9) : 6463 -6482.

PDF (831KB)
Electronic Research Archive ›› 2026, Vol. 34 ›› Issue (9) :6463 -6482. DOI: 10.3934/era.2026283
Research article
research-article
A satisfactory consistency judging method of linguistic judgment matrix based on transitive closure
Author information +
History +
PDF (831KB)

Abstract

Language phrases are effective tools for depicting uncertain information and are highly consistent with the cognitive habits and expression needs of decision-makers when they evaluate things using natural language. During the decision-making process, decision-makers can compare the alternative options in pairs to obtain a linguistic judgment matrix. First, the comparative preference relationship among schemes is regarded as a binary relation on the set of decision schemes. The preference relation matrix derived from the linguistic judgment matrix is, in essence, the matrix-based expression of this set relation. From the perspective of relational transitivity, if the transitive closure of this set relation coincides with the preference relation matrix, meaning the relation possesses complete transitivity, the linguistic judgment matrix can be determined to meet the requirement of satisfactory consistency. Second, if decision-makers have logical conflicts in pairwise comparisons, the corresponding linguistic judgment matrix will inevitably fail to satisfy the satisfactory consistency condition. For the precise identification of such logical contradictions, the second-order submatrix derived from the preference relation matrix within the linguistic judgment matrix is amenable to application. This submatrix can represent illogical preference judgments formed by 3 or 4 decision schemes. Therefore, by examining whether there exists an illogical preference structure in the second-order submatrix, we could inversely infer whether the original linguistic judgment matrix possesses satisfactory consistency. We conducted analysis combined with decision cases, confirming the feasibility and application value of this theoretical framework from the perspective of case application.

Keywords

linguistic judgment matrix / loop matrix / satisfactory consistency / transitive closure / ranking matrix

Cite this article

Download citation ▾
Yunlong Zhang, Fengxia Jin, Jingfei Jiang, Juan LG Guirao, Huatao Chen. A satisfactory consistency judging method of linguistic judgment matrix based on transitive closure. Electronic Research Archive, 2026, 34 (9) : 6463-6482 DOI:10.3934/era.2026283

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

M. Ranjbar, S. Effati, Group decision making in the analytic hierarchy process by hesitant fuzzy numbers, Sci. Rep., 13 (2023), 21864. https://doi.org/10.1038/S41598-023-49076-3

[2]

J. Górecki, D. Bartl, J. Ramík, Robustness of priority deriving methods for pairwise comparison matrices against rank reversal: A probabilistic approach, Ann. Oper. Res., 333 (2024), 249-273. https://doi.org/10.1007/S10479-023-05753-0

[3]

Y. Xu, Y. L. Fu, Y. Chen, K. K. Lai, Multicriteria ABC inventory classification using a group decision making method with individual preferences, Asia-Pac. J. Oper. Res., 40 (2023), 2250036. https://doi.org/10.1142/S0217595922500361

[4]

S. Kaashi, A. Vilventhan, Development of a building information modelling based decision-making framework for green retrofitting of existing buildings, J. Build. Eng., 80 (2023), 108128. https://doi.org/10.1016/J.JOBE.2023.108128

[5]

Y. Wang, L. Zhou, H. Li, X. Dai, Probabilistic consistency of stochastic multiplicative comparison matrices based on Monte Carlo simulation, Inf. Sci., 656 (2024), 119896. https://doi.org/10.1016/J.INS.2023.119896

[6]

L. Jing, H. Zhang, Y. Dou, D. Feng, W. Jia, S. Jiang, Conceptual design decision-making considering multigranularity heterogeneous evaluation semantics with uncertain beliefs, Expert Syst. Appl., 244 (2024), 122963. https://doi.org/10.1016/J.ESWA.2023.122963

[7]

M. T. Aljburi, A. S. Albahri, O. S. Albahri, A. H. Alamoodi, S. M. Mohammed, M. Deveci, et al., Exploring decision-making techniques for evaluation and benchmarking of energy system integration frameworks for achieving a sustainable energy future, Energy Strategy Rev., 51 (2024), 101251. https://doi.org/10.1016/J.ESR.2023.101251

[8]

M. Islam, S. A. Al-Sobhi, A. Naquash, M. A. Qyyum, M. Lee, Optimal process selection for natural gas liquids recovery: Energy, exergy, economic, and environmental perspectives, Energy, 289 (2024), 129757. https://doi.org/10.1016/J.ENERGY.2023.129757

[9]

S. Lai, Z. Wu, J. Wu, C. Ye, Z. Wang, Z. Ma, Multimodal fuzzy semantic fusion modeling for community disaster damage assessment from social sensing, Inf. Fusion, 127 (2026) 103879. https://doi.org/10.1016/j.inffus.2025.103879

[10]

W. Chang, N. Zhang, H. Ren, C. Fu, Filtration-and-weighting-based triangular bounded consistency of interval-valued fuzzy preference relations, Fuzzy Sets Syst., 519 (2025), 109524. https://doi.org/10.1016/J.FSS.2025.109524

[11]

J. Li, J. Cui, Q. Su, Boosting fuzzy classification rules under footprint of uncertainty of type-2 fuzzy sets, Appl. Soft Comput., 185 (2025), 113876. https://doi.org/10.1016/J.ASOC.2025.113876

[12]

J. Wang, X. Zhang, L. Mao, An OWA-based multi-granulation fuzzy rough set model using Choquet integrals and its applications, Fuzzy Sets Syst., 521 (2025), 109595. https://doi.org/10.1016/J.FSS.2025.109595

[13]

C. Wu, Y. Gao, Generalized multiplicative interval type-2 fuzzy partition C-means clustering, Inf. Sci., 718 (2025), 122356. https://doi.org/10.1016/J.INS.2025.122356

[14]

G. Zhang, Y. Shi, W. Yao, Convexity structures of the Hausdorff fuzzy quasi-metric spaces, Inf. Sci., 718 (2025), 122406. https://doi.org/10.1016/J.INS.2025.122406

[15]

T. Y. Chen, ORESTE methodology within a circular intuitionistic fuzzy framework for preferential outranking in hybrid cloud service selection, Appl. Soft Comput., 185 (2025), 113864. https://doi.org/10.1016/J.ASOC.2025.113864

[16]

A. Nik-Khorasani, M. R. Akbarzadeh-T, Reliable Type 2 Fuzzy Min-Max neural networks for pattern classification, Appl. Soft Comput., 185 (2025), 113875. https://doi.org/10.1016/J.ASOC.2025.113875

[17]

H. Liao, X. Li, Y. Cheng, L. Luo, D. Liu, A multiattribute decision-making framework for multidisciplinary lung cancer treatment considering expert willingness for opinion transformation, IEEE Trans. Cybern., 56 (2026), 497-508. https://doi.org/10.1109/TCYB.2025.3612413

[18]

X. Xiao, Z. Xu, W. Gan, T. Wu, Y. Zheng, Probabilistic linguistic convolutional neural network dealing with low-quality image classification, IEEE Trans. Fuzzy Syst., 33 (2025), 1678-1690. https://doi.org/10.1109/TFUZZ.2025.3534903

[19]

T. Wang, H. Zhu, B. Huang, Weighted group role assignment based on three-way conflict analysis with interval-valued intuitionistic fuzzy numbers, IEEE Trans. Cybern., 56 (2026), 853-866. https://doi.org/10.1109/TCYB.2025.3623995

[20]

K. Woźniak, M. R. Ogiela, L. Ogiela, Multi-criteria linguistic optimization for covert communication in secure LLM-based steganography, Appl. Soft Comput., 185 (2025), 113960. https://doi.org/10.1016/J.ASOC.2025.113960

[21]

S. Stanimirović, L. A. Nguyen, M. Ćirić, M. Stanković, Approximate state reduction of fuzzy finite automata, Fuzzy Sets Syst., 519 (2025), 109535. https://doi.org/10.1016/j.fss.2025.109535

[22]

Y. Xu, Z. Chen, W. Li, Y. Wu, Exponential stability of fractional-order fuzzy multilayer networks with short memory and non-instantaneous impulses via intermittent control, IEEE Trans. Fuzzy Syst., 33 (2025), 1639-1649. https://doi.org/10.1109/TFUZZ.2025.3528975

[23]

S. Barhoumi, I. K. Kallel, E. Bossé, B. Solaiman, An empirical survey-type analysis of uncertainty measures for the fusion of crisp and fuzzy bodies of evidence, Inf. Fusion, 121 (2025), 103106. https://doi.org/10.1016/j.inffus.2025.103106

[24]

X. Jiang, L. Ou, Y. Chen, N. Ao, Y. Chang, T. Do, et al., A fuzzy logic-based approach to predict human interaction by functional near-infrared spectroscopy, IEEE Trans. Fuzzy Syst., 33 (2025), 1664-1677. https://doi.org/10.1109/TFUZZ.2025.3528376

[25]

C. Zhang, G. Xue, W. Xu, H. Zhi, Y. Zhou, E. C. C. Tsang, Association-based concept-cognitive learning for classification: Fusing knowledge with distance metric learning, Inf. Fusion, 124 (2025), 103386. https://doi.org/10.1016/j.inffus.2025.103386

[26]

Y. Tang, J. Gao, W. Pedrycz, X. Han, F. Ren, Differently implicational Bandler-Kohout subproduct method, IEEE Trans. Cybern., 55 (2025), 5421-5434. https://doi.org/10.1109/TCYB.2025.3599631

[27]

G. C. Yalçın, Development of a fuzzy-based decision support system for sustainable tractor selection in green ports, Facta Univ. Ser. Mech. Eng., 23 (2025), 579-604. https://doi.org/10.22190/FUME250610029Y

[28]

S. Śniegowski, A. Świder, A. Shekhovtsov, W. Sałabun, Modeling uncertainty in engineering problems using asymmetric interval numbers (AINs), Spectr. Mech. Eng. Oper. Res., 3 (2026), 28-41. https://doi.org/10.31181/smeor31202651

[29]

K. Wang, L. Cheng, M. Yin, K. Zhang, R. Wang, M. Zhang, et al., Evolutionary game theory in energy storage systems: A systematic review of collaborative decision-making, operational strategies, and coordination mechanisms for renewable energy integration, Sustainability, 17 (2025), 7400. https://doi.org/10.3390/su17167400

[30]

L. Cheng, M. Li, C. Tan, P. Huang, M. Zhang, R. Sun, Computational game-theoretic models for adaptive urban energy systems: A comprehensive review of algorithms, strategies, and engineering applications, Arch. Comput. Methods Eng., 33 (2026), 2037-2114. https://doi.org/10.1007/s11831-025-10364-y

[31]

L. Cheng, M. Zhang, K. Wang, M. Yuan, Z. Liu, J. Wang, et al., Evolutionary smart contracts for virtual power plant trading: Integrating prospect theory and multi-stage negotiation in cross-regional energy markets, Int. J. Electr. Power Energy Syst., 173 (2025), 111453. https://doi.org/10.1016/j.ijepes.2025.111453

PDF (831KB)

0

Accesses

0

Citation

Detail

Sections
Recommended

/

〈 〉