IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v322y2025i2p615-628.html
   My bibliography  Save this article

Optimal ranking model of fuzzy preference relations with self-confidence for addressing self-confidence failure

Author

Listed:
  • Zhang, Chonghui
  • Luo, Dandan
  • Su, Weihua
  • Benjamin, Lev

Abstract

Fuzzy preference relation with self-confidence (FPR-SC) uses semantic self-confidence to illustrate the hesitation of experts in affirming given preference values. However, extant ranking derivation methods of FPRs-SC suffer from self-confidence failure problem. Specifically, when the logical operations of self-confidence levels are replaced by algebraic operations on semantic subscripts, the derived rankings may be unstable or independent of the self-confidence. To address this issue, an optimal ranking model of FPR-SC with chance-constrained is proposed and extended to group decision-making. Based on the concept of ‘reliability level’ in parameter estimation, the evaluation information expressed by ‘preference values + self-confidence levels’ is first explained using probability distributions to achieve dimensional unity between qualitative self-confidence and quantitative preference. A multiplicative consistency-driven optimal model is then designed to assess the individuality of self-confidence. Guided by the ‘3σ’ principle, FPR-SC is further replaced by random variables following asymmetric bilateral truncated normal distributions. This transformation captures the inner cognition of individuals during subjective judgment, and ensures effective constraints on the numerical range through the asymmetric design. Finally, motivated by the minimization of information deviation, an FPR-SC optimal ranking model with chance-constrained is constructed, and its effectiveness is verified.

Suggested Citation

  • Zhang, Chonghui & Luo, Dandan & Su, Weihua & Benjamin, Lev, 2025. "Optimal ranking model of fuzzy preference relations with self-confidence for addressing self-confidence failure," European Journal of Operational Research, Elsevier, vol. 322(2), pages 615-628.
    • Handle: RePEc:eee:ejores:v:322:y:2025:i:2:p:615-628
    DOI: 10.1016/j.ejor.2024.11.011
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221724008580
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2024.11.011?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Xunjie Gou & Zeshui Xu & Xinxin Wang & Huchang Liao, 2021. "Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 51-79, March.
    2. Zhi Chen & Daniel Kuhn & Wolfram Wiesemann, 2024. "Technical Note—Data-Driven Chance Constrained Programs over Wasserstein Balls," Operations Research, INFORMS, vol. 72(1), pages 410-424, January.
    3. Maxime C. Cohen & Philipp W. Keller & Vahab Mirrokni & Morteza Zadimoghaddam, 2019. "Overcommitment in Cloud Services: Bin Packing with Chance Constraints," Management Science, INFORMS, vol. 65(7), pages 3255-3271, July.
    4. Zaiwu Gong & Xiao Tan & Yingjie Yang, 2019. "Optimal weighting models based on linear uncertain constraints in intuitionistic fuzzy preference relations," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(8), pages 1296-1307, August.
    5. Miguel A. Lejeune & François Margot, 2016. "Solving Chance-Constrained Optimization Problems with Stochastic Quadratic Inequalities," Operations Research, INFORMS, vol. 64(4), pages 939-957, August.
    6. Wenqi Liu & Hengjie Zhang & Haiming Liang & Cong-cong Li & Yucheng Dong, 2022. "Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method," Group Decision and Negotiation, Springer, vol. 31(1), pages 213-240, February.
    7. Biljana N. Adebambo & Xuemin (Sterling) Yan, 2018. "Investor Overconfidence, Firm Valuation, and Corporate Decisions," Management Science, INFORMS, vol. 64(11), pages 5349-5369, November.
    8. Zhen Zhang & Xinyue Kou & Wenyu Yu & Yuan Gao, 2021. "Consistency improvement for fuzzy preference relations with self-confidence: An application in two-sided matching decision making," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(8), pages 1914-1927, August.
    9. Wenqi Liu & Yucheng Dong & Francisco Chiclana & Francisco Javier Cabrerizo & Enrique Herrera-Viedma, 2017. "Group decision-making based on heterogeneous preference relations with self-confidence," Fuzzy Optimization and Decision Making, Springer, vol. 16(4), pages 429-447, December.
    10. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Shanshan & Mehrotra, Sanjay & Peng, Chun, 2025. "Robust concave utility maximization over chance constraints," European Journal of Operational Research, Elsevier, vol. 321(3), pages 800-813.
    2. Xiaodi Bai & Jie Sun & Xiaojin Zheng, 2021. "An Augmented Lagrangian Decomposition Method for Chance-Constrained Optimization Problems," INFORMS Journal on Computing, INFORMS, vol. 33(3), pages 1056-1069, July.
    3. Gong, Zaiwu & Guo, Weiwei & Herrera-Viedma, Enrique & Gong, Zejun & Wei, Guo, 2020. "Consistency and consensus modeling of linear uncertain preference relations," European Journal of Operational Research, Elsevier, vol. 283(1), pages 290-307.
    4. Anand Deo & Karthyek Murthy, 2025. "The Scaling Behaviors in Achieving High Reliability via Chance-Constrained Optimization," Papers 2504.07728, arXiv.org.
    5. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    6. Sander Claeys & Marta Vanin & Frederik Geth & Geert Deconinck, 2021. "Applications of optimization models for electricity distribution networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    7. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    8. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    9. Hermann Held, 2019. "Cost Risk Analysis: Dynamically Consistent Decision-Making under Climate Targets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 247-261, January.
    10. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
    11. Wu, Desheng (Dash) & Lee, Chi-Guhn, 2010. "Stochastic DEA with ordinal data applied to a multi-attribute pricing problem," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1679-1688, December.
    12. Wenqi Liu & Hengjie Zhang & Haiming Liang & Cong-cong Li & Yucheng Dong, 2022. "Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method," Group Decision and Negotiation, Springer, vol. 31(1), pages 213-240, February.
    13. Odetayo, Babatunde & MacCormack, John & Rosehart, William D. & Zareipour, Hamidreza, 2017. "A sequential planning approach for Distributed generation and natural gas networks," Energy, Elsevier, vol. 127(C), pages 428-437.
    14. Wang, S. & Huang, G.H., 2014. "An integrated approach for water resources decision making under interactive and compound uncertainties," Omega, Elsevier, vol. 44(C), pages 32-40.
    15. Ghazale Kordi & Parsa Hasanzadeh-Moghimi & Mohammad Mahdi Paydar & Ebrahim Asadi-Gangraj, 2023. "A multi-objective location-routing model for dental waste considering environmental factors," Annals of Operations Research, Springer, vol. 328(1), pages 755-792, September.
    16. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    17. Giada Spaccapanico Proietti & Mariagiulia Matteucci & Stefania Mignani & Bernard P. Veldkamp, 2024. "Chance-Constrained Automated Test Assembly," Journal of Educational and Behavioral Statistics, , vol. 49(1), pages 92-120, February.
    18. Jana, R.K. & Sharma, Dinesh K. & Chakraborty, B., 2016. "A hybrid probabilistic fuzzy goal programming approach for agricultural decision-making," International Journal of Production Economics, Elsevier, vol. 173(C), pages 134-141.
    19. Rocchetta, Roberto & Crespo, Luis G., 2021. "A scenario optimization approach to reliability-based and risk-based design: Soft-constrained modulation of failure probability bounds," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    20. Bilsel, R. Ufuk & Ravindran, A., 2011. "A multiobjective chance constrained programming model for supplier selection under uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1284-1300, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:322:y:2025:i:2:p:615-628. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.