Skip to main content
Log in

Three-way group conflict analysis based on q-rung orthopair fuzzy set theory

  • Published:
Computational and Applied Mathematics Aims and scope Submit manuscript

Abstract

Many researches introduce fuzzy sets to describe vague and uncertain information in conflict analysis, and build fuzzy information systems to depict attitudes of agents toward issues. q-rung orthopair fuzzy set as a generalization of Pythagorean fuzzy set is more powerful and efficient in information representation. In this paper, we propose two conflict analysis models based on q-rung orthopair fuzzy information system and corresponding discern functions, and employ examples to illustrate the ability of partition agent set into three different nonempty alliances. For the construction of dynamic conflict analysis model, we study the change of classification of agent set with the variation of q. In the meanwhile, we find that the changed classification can not be the same with the original classification in some cases. The occurrence of such situation is related to discern functions. Thus, we introduce overlap functions as discern functions, and employ examples to illustrate overlap functions can keep the classification of agent set in the cases, which other discern functions fail to maintain.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Ali MI (2018) Another view on \(q\)-rung orthopair fuzzy sets. Int J Intell Syst 33(11):2139–2153

    Google Scholar 

  • Ali Z, Mahmood T (2020) Maclaurin symmetric mean operators and their applications in the environment of complex \(q\)-rung orthopair fuzzy sets. Comput Appl Math 39(3):1–27

    MathSciNet  MATH  Google Scholar 

  • Ali A, Ali MI, Rehman N (2019) Soft dominance based rough sets with applications in information systems. Int J Approx Reason 113:171–195

    MathSciNet  MATH  Google Scholar 

  • Bashir Z, Mahnaz S, Abbas Malik MG (2021) Conflict resolution using game theory and rough sets. Int J Intell Syst 36(1):237–259

    Google Scholar 

  • Bashir Z, Wahab A, Rashid T (2022) Three-way decision with conflict analysis approach in the framework of fuzzy set theory. Soft Comput 26(1):309–326

    Google Scholar 

  • Bustince H, Fernandez J, Mesiar R et al (2010) Overlap functions. Nonlinear Anal Theory Methods Appl 72(3–4):1488–1499

    MathSciNet  MATH  Google Scholar 

  • Bustince H, Pagola M, Mesiar R et al (2011) Grouping, overlap, and generalized bientropic functions for fuzzy modeling of pairwise comparisons. IEEE Trans Fuzzy Syst 20(3):405–415

    Google Scholar 

  • Bustince H, Mesiar R, Dimuro G et al (2021) The evolution of the notion of overlap functions. In: Fuzzy approaches for soft computing and approximate reasoning: theories and applications. Springer, Berlin, pp 21–29

  • da Cruz Asmus T, Dimuro GP, Bedregal B et al (2020) General interval-valued overlap functions and interval-valued overlap indices. Inf Sci 527:27–50

    MathSciNet  MATH  Google Scholar 

  • Da Silva IA, Bedregal B, Bustince H (2015) Weighted average operators generated by \(n\)-dimensional overlaps and an application in decision. In: 2015 conference of the international fuzzy systems association and the European society for fuzzy logic and technology (IFSA-EUSFLAT-15). Atlantis Press, London, pp 1473–1478

  • de Oliveira Silva LG, de Almeida-Filho AT (2016) A multicriteria approach for analysis of conflicts in evidence theory. Inf Sci 346:275–285

    MATH  Google Scholar 

  • Deja R (2000) Conflict analysis. In: Rough set methods and applications. Springer, London, pp 491–519

  • Dimuro GP, Fernández J, Bedregal B et al (2020a) The state-of-art of the generalizations of the Choquet integral: from aggregation and pre-aggregation to ordered directionally monotone functions. Inform Fusion 57:27–43

  • Dimuro GP, Lucca G, Bedregal B et al (2020b) Generalized CF1F2-integrals: from Choquet-like aggregation to ordered directionally monotone functions. Fuzzy Sets Syst 378:44–67

  • Du WS (2018) Minkowski-type distance measures for generalized orthopair fuzzy sets. Int J Intell Syst 33(4):802–817

    Google Scholar 

  • Du J, Liu S, Liu Y et al (2022) A novel approach to three-way conflict analysis and resolution with Pythagorean fuzzy information. Inf Sci 584:65–88

    Google Scholar 

  • Elkano M, Galar M, Sanz JA et al (2014) Enhancing multiclass classification in FARC-HD fuzzy classifier: on the synergy between \(n\)-dimensional overlap functions and decomposition strategies. IEEE Trans Fuzzy Syst 23(5):1562–1580

    Google Scholar 

  • Elkano M, Galar M, Sanz J et al (2016) Fuzzy rule-based classification systems for multi-class problems using binary decomposition strategies: on the influence of \(n\)-dimensional overlap functions in the fuzzy reasoning method. Inf Sci 332:94–114

    Google Scholar 

  • Elkano M, Galar M, Sanz JA et al (2018) Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems. Appl Soft Comput 67:728–740

    Google Scholar 

  • Garcia-Jimenez S, Bustince H, Huellermeier E et al (2014) Overlap indices: construction of and application to interpolative fuzzy systems. IEEE Trans Fuzzy Syst 23(4):1259–1273

    Google Scholar 

  • Garcia-Jimenez S, Jurio A, Pagola M et al (2017) Forest fire detection: a fuzzy system approach based on overlap indices. Appl Soft Comput 52:834–842

    Google Scholar 

  • Garg H, Chen SM (2020) Multiattribute group decision making based on neutrality aggregation operators of \(q\)-rung orthopair fuzzy sets. Inf Sci 517:427–447

    MathSciNet  MATH  Google Scholar 

  • Gomez D, Rodríguez JT, Yanez J et al (2016) A new modularity measure for fuzzy community detection problems based on overlap and grouping functions. Int J Approx Reason 74:88–107

    MathSciNet  MATH  Google Scholar 

  • Jurio A, Bustince H, Pagola M et al (2013) Some properties of overlap and grouping functions and their application to image thresholding. Fuzzy Sets Syst 229:69–90

    MathSciNet  MATH  Google Scholar 

  • Kamacı H, Petchimuthu S (2022) Some similarity measures for interval-valued bipolar \(q\)-rung orthopair fuzzy sets and their application to supplier evaluation and selection in supply chain management. Environ Develop Sustain 2022:1–40

    Google Scholar 

  • Lang G (2020) A general conflict analysis model based on three-way decision. Int J Mach Learn Cybern 11(5):1083–1094

    Google Scholar 

  • Lang G (2021) Three-way conflict analysis: alliance, conflict, and neutrality reducts of three-valued situation tables. Cogn Comput 2021:1–14

    Google Scholar 

  • Lang G, Yao Y (2021) New measures of alliance and conflict for three-way conflict analysis. Int J Approx Reason 132:49–69

    MathSciNet  MATH  Google Scholar 

  • Lang G, Miao D, Cai M (2017) Three-way decision approaches to conflict analysis using decision-theoretic rough set theory. Inf Sci 406:185–207

    MATH  Google Scholar 

  • Lang G, Miao D, Fujita H (2019) Three-way group conflict analysis based on Pythagorean fuzzy set theory. IEEE Trans Fuzzy Syst 28(3):447–461

    Google Scholar 

  • Lang G, Luo J, Yao Y (2020) Three-way conflict analysis: a unification of models based on rough sets and formal concept analysis. Knowl-Based Syst 194(105):556

    Google Scholar 

  • Li X, Wang X, Lang G et al (2021) Conflict analysis based on three-way decision for triangular fuzzy information systems. Int J Approx Reason 132:88–106

    MathSciNet  MATH  Google Scholar 

  • Li X, Yang Y, Yi H et al (2022) Conflict analysis based on three-way decision for trapezoidal fuzzy information systems. Int J Mach Learn Cybern 13(4):929–945

    Google Scholar 

  • Liu Y, Lin Y (2015) Intuitionistic fuzzy rough set model based on conflict distance and applications. Appl Soft Comput 31:266–273

    Google Scholar 

  • Liu P, Liu W (2019) Multiple-attribute group decision-making based on power bonferroni operators of linguistic \(q\)-rung orthopair fuzzy numbers. Int J Intell Syst 34(4):652–689

    Google Scholar 

  • Liu P, Wang P (2018) Multiple-attribute decision-making based on Archimedean Bonferroni operators of \(q\)-rung orthopair fuzzy numbers. IEEE Trans Fuzzy Syst 27(5):834–848

    Google Scholar 

  • Lucca G, Dimuro GP, Mattos V et al (2015) A family of Choquet-based non-associative aggregation functions for application in fuzzy rule-based classification systems. In: 2015 IEEE international conference on fuzzy systems (FUZZ-IEEE). IEEE, London, pp 1–8

  • Lucca G, Sanz JA, Dimuro GP et al (2017) Cc-integrals: Choquet-like copula-based aggregation functions and its application in fuzzy rule-based classification systems. Knowl-Based Syst 119:32–43

    Google Scholar 

  • Lucca G, Dimuro GP, Fernández J et al (2018a) Improving the performance of fuzzy rule-based classification systems based on a nonaveraging generalization of cc-integrals named \(c_{F_1 F_2}\)-integrals. IEEE Trans Fuzzy Syst 27(1):124–134

  • Lucca G, Sanz JA, Dimuro GP et al (2018b) Cf-integrals: a new family of pre-aggregation functions with application to fuzzy rule-based classification systems. Inf Sci 435:94–110

  • Lucca G, Sanz JA, Dimuro GP et al (2020) A proposal for tuning the \(\alpha \) parameter in \(c_\alpha c\)-integrals for application in fuzzy rule-based classification systems. Nat Comput 9(3):533–546

    Google Scholar 

  • Nolasco DH, Costa FB, Palmeira ES et al (2019) Wavelet-fuzzy power quality diagnosis system with inference method based on overlap functions: case study in an ac microgrid. Eng Appl Artif Intell 85:284–294

    Google Scholar 

  • Paternain D, Bustince H, Pagola M et al (2016) Capacities and overlap indexes with an application in fuzzy rule-based classification systems. Fuzzy Sets Syst 305:70–94

    MathSciNet  MATH  Google Scholar 

  • Pawlak Z (1984) On conflicts. Int J Man Mach Stud 21(2):127–134

    MATH  Google Scholar 

  • Pawlak Z (1998) An inquiry into anatomy of conflicts. Inf Sci 109(1–4):65–78

    MathSciNet  Google Scholar 

  • Pawlak Z (2005) Some remarks on conflict analysis. Eur J Oper Res 166(3):649–654

    MATH  Google Scholar 

  • Pawlak Z, Skowron A (2007) Rough sets and Boolean reasoning. Inf Sci 177(1):41–73

    MathSciNet  MATH  Google Scholar 

  • Peng X, Liu L (2019) Information measures for \(q\)-rung orthopair fuzzy sets. Int J Intell Syst 34(8):1795–1834

    Google Scholar 

  • Przybyła-Kasperek M (2019) Three conflict methods in multiple classifiers that use dispersed knowledge. Int J Inf Technol Decis Making 18(02):555–599

    Google Scholar 

  • Przybyła-Kasperek M (2020) Coalitions weights in a dispersed system with Pawlak conflict model. Group Decis Negot 29(3):549–591

    Google Scholar 

  • Qi J, Wei L, Ren R (2021) 3-way concept analysis based on 3-valued formal contexts. Cogn Comput 2021:1–13

    Google Scholar 

  • Rehman N, Ali A, Ali Shah SI et al (2019) Variable precision multi decision \(\lambda \)-soft dominance based rough sets and their applications in conflict problems. J Intell Fuzzy Syst 36(6):5345–5360

    Google Scholar 

  • Rehman N, Ali A, Hila K (2020) Soft dominance based multigranulation decision theoretic rough sets and their applications in conflict problems. Artif Intell Rev 53(8):6079–6110

    Google Scholar 

  • Santos H, Lima L, Bedregal B et al (2015) Analyzing subdistributivity and superdistributivity on overlap and grouping functions. In: Proceedings of the 8th international summer school on aggregation operators (AGOP 2015), pp 211–216

  • Sun B, Ma W (2015) Rough approximation of a preference relation by multi-decision dominance for a multi-agent conflict analysis problem. Inf Sci 315:39–53

    MathSciNet  MATH  Google Scholar 

  • Sun B, Ma W, Zhao H (2016) Rough set-based conflict analysis model and method over two universes. Inf Sci 372:111–125

    MATH  Google Scholar 

  • Sun B, Chen X, Zhang L et al (2020) Three-way decision making approach to conflict analysis and resolution using probabilistic rough set over two universes. Inf Sci 507:809–822

    MathSciNet  MATH  Google Scholar 

  • Tong S, Sun B, Chu X et al (2021) Trust recommendation mechanism-based consensus model for Pawlak conflict analysis decision making. Int J Approx Reason 135:91–109

    MathSciNet  MATH  Google Scholar 

  • Wang P, Wang J, Wei G et al (2019) Similarity measures of \(q\)-rung orthopair fuzzy sets based on cosine function and their applications. Mathematics 7(4):1–23

    Google Scholar 

  • Wei G, Wei C, Wang J et al (2019) Some \(q\)-rung orthopair fuzzy maclaurin symmetric mean operators and their applications to potential evaluation of emerging technology commercialization. Int J Intell Syst 34(1):50–81

    Google Scholar 

  • Xing Y, Zhang R, Zhou Z et al (2019) Some \(q\)-rung orthopair fuzzy point weighted aggregation operators for multi-attribute decision making. Soft Comput 23(22):11627–11649

    MATH  Google Scholar 

  • Xu L, Liu Y, Liu H (2019) Some improved \(q\)-rung orthopair fuzzy aggregation operators and their applications to multiattribute group decision-making. Math Problems Eng 2019:1

    MathSciNet  MATH  Google Scholar 

  • Xu F, Cai M, Song H et al (2022) The selection of feasible strategies based on consistency measurement of cliques. Inf Sci 583:33–55

    Google Scholar 

  • Yager RR (2016) Generalized orthopair fuzzy sets. IEEE Trans Fuzzy Syst 25(5):1222–1230

    Google Scholar 

  • Yager RR, Abbasov AM (2013) Pythagorean membership grades, complex numbers, and decision making. Int J Intell Syst 28(5):436–452

    Google Scholar 

  • Yager Ronald R (2013) Pythagorean membership grades in multicriteria decision making. IEEE Trans Fuzzy Syst 22(4):958–965

    Google Scholar 

  • Yang W, Pang Y (2019) New \(q\)-rung orthopair fuzzy partitioned Bonferroni mean operators and their application in multiple attribute decision making. Int J Intell Syst 34(3):439–476

    Google Scholar 

  • Yao Y (2010) Three-way decisions with probabilistic rough sets. Inf Sci 180(3):341–353

    MathSciNet  Google Scholar 

  • Yao Y (2019) Three-way conflict analysis: reformulations and extensions of the Pawlak model. Knowl-Based Syst 180:26–37

    Google Scholar 

  • Yi H, Zhang H, Li X et al (2021) Three-way conflict analysis based on hesitant fuzzy information systems. Int J Approx Reason 139:12–27

    MathSciNet  MATH  Google Scholar 

  • Zhang Z, Chen SM (2021) Group decision making with incomplete \(q\)-rung orthopair fuzzy preference relations. Inf Sci 553:376–396

    MathSciNet  MATH  Google Scholar 

  • Zhi H, Qi J, Qian T et al (2020) Conflict analysis under one-vote veto based on approximate three-way concept lattice. Inf Sci 516:316–330

    MathSciNet  Google Scholar 

Download references

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant No. 12101500) and the Chinese Universities Scientific Fund (Grant Nos. 2452018054 and 2452022370).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bin Yang.

Ethics declarations

Conflict of interest

No potential conflict of interest was reported by the authors.

Additional information

Communicated by Graçaliz Pereira Dimuro.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lin, T., Yang, B. Three-way group conflict analysis based on q-rung orthopair fuzzy set theory. Comp. Appl. Math. 42, 30 (2023). https://doi.org/10.1007/s40314-022-02177-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s40314-022-02177-7

Keywords

Mathematics Subject Classification

Navigation