IDEAS home Printed from https://ideas.repec.org/a/wly/jnljam/v2012y2012i1n136254.html

Intuitionistic Fuzzy Normalized Weighted Bonferroni Mean and Its Application in Multicriteria Decision Making

Author

Listed:
  • Wei Zhou
  • Jian-min He

Abstract

The Bonferroni mean (BM) was introduced by Bonferroni six decades ago but has been a hot research topic recently since its usefulness of the aggregation techniques. The desirable characteristic of the BM is its capability to capture the interrelationship between input arguments. However, the classical BM and GBM ignore the weight vector of aggregated arguments, the general weighted BM (WBM) has not the reducibility, and the revised generalized weighted BM (GWBM) cannot reflect the interrelationship between the individual criterion and other criteria. To deal with these issues, in this paper, we propose the normalized weighted Bonferroni mean (NWBM) and the generalized normalized weighted Bonferroni mean (GNWBM) and study their desirable properties, such as reducibility, idempotency, monotonicity, and boundedness. Furthermore, we investigate the NWBM and GNWBM operators under the intuitionistic fuzzy environment which is more common phenomenon in modern life and develop two new intuitionistic fuzzy aggregation operators based on the NWBM and GNWBM, that is, the intuitionistic fuzzy normalized weighted Bonferroni mean (IFNWBM) and the generalized intuitionistic fuzzy normalized weighted Bonferroni mean (GIFNWBM). Finally, based on the GIFNWBM, we propose an approach to multicriteria decision making under the intuitionistic fuzzy environment, and a practical example is provided to illustrate our results.

Suggested Citation

  • Wei Zhou & Jian-min He, 2012. "Intuitionistic Fuzzy Normalized Weighted Bonferroni Mean and Its Application in Multicriteria Decision Making," Journal of Applied Mathematics, John Wiley & Sons, vol. 2012(1).
  • Handle: RePEc:wly:jnljam:v:2012:y:2012:i:1:n:136254
    DOI: 10.1155/2012/136254
    as

    Download full text from publisher

    File URL: https://doi.org/10.1155/2012/136254
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2012/136254?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
    ---><---

    References listed on IDEAS

    as
    1. Michel Grabisch & Jean-Luc Marichal & Radko Mesiar & Endre Pap, 2009. "Aggregation functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00445120, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ya-ming Shi & Jian-min He, 2013. "The Interval‐Valued Intuitionistic Fuzzy Optimized Weighted Bonferroni Means and Their Application," Journal of Applied Mathematics, John Wiley & Sons, vol. 2013(1).
    2. Wei Zhou, 2014. "On Hesitant Fuzzy Reducible Weighted Bonferroni Mean and Its Generalized Form for Multicriteria Aggregation," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).
    3. Dejian Yu, 2014. "Hydrogen Production Technologies Evaluation Based on Interval‐Valued Intuitionistic Fuzzy Multiattribute Decision Making Method," Journal of Applied Mathematics, John Wiley & Sons, vol. 2014(1).

    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. Luca Anzilli & Silvio Giove, 2020. "Multi-criteria and medical diagnosis for application to health insurance systems: a general approach through non-additive measures," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 43(2), pages 559-582, December.
    2. Ya-Qiang Xu & Le-Sheng Jin & Zhen-Song Chen & Ronald R. Yager & Jana Špirková & Martin Kalina & Surajit Borkotokey, 2022. "Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information," Mathematics, MDPI, vol. 10(4), pages 1-11, February.
    3. Peter Reichert & Klemens Niederberger & Peter Rey & Urs Helg & Susanne Haertel-Borer, 2019. "The need for unconventional value aggregation techniques: experiences from eliciting stakeholder preferences in environmental management," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 197-219, November.
    4. Grabisch, Michel & Rusinowska, Agnieszka, 2013. "A model of influence based on aggregation functions," Mathematical Social Sciences, Elsevier, vol. 66(3), pages 316-330.
    5. Vicenç Torra, 2022. "Andness Directedness for t-Norms and t-Conorms," Mathematics, MDPI, vol. 10(9), pages 1-10, May.
    6. Chunqiao Tan & Xiaohong Chen, 2016. "Generalized Archimedean Intuitionistic Fuzzy Averaging Aggregation Operators and their Application to Multicriteria Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 15(02), pages 311-352, March.
    7. José Luis García-Lapresta & Casilda Lasso de la Vega & Ricardo Alberto Marques Pereira & Ana Marta Urrutia, 2010. "A class of poverty measures induced by the dual decomposition of aggregation functions," Working Papers 160, ECINEQ, Society for the Study of Economic Inequality.
    8. Bonifacio Llamazares, 2019. "An Analysis of Winsorized Weighted Means," Group Decision and Negotiation, Springer, vol. 28(5), pages 907-933, October.
    9. Marco LiCalzi & M. Alperen Yasar, 2024. "Vocabulary aggregation," Working Papers 06, Venice School of Management - Department of Management, Università Ca' Foscari Venezia.
    10. Karlson Pfannschmidt & Pritha Gupta & Bjorn Haddenhorst & Eyke Hullermeier, 2019. "Learning Context-Dependent Choice Functions," Papers 1901.10860, arXiv.org, revised Oct 2021.
    11. Fabrizio Durante & Juan Fernández-Sánchez & Wolfgang Trutschnig & Manuel Úbeda-Flores, 2020. "On the Size of Subclasses of Quasi-Copulas and Their Dedekind–MacNeille Completion," Mathematics, MDPI, vol. 8(12), pages 1-11, December.
    12. Belles-Sampera, Jaume & Merigó, José M. & Guillén, Montserrat & Santolino, Miguel, 2013. "The connection between distortion risk measures and ordered weighted averaging operators," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 411-420.
    13. Saminger-Platz Susanne & De Jesús Arias-García José & Mesiar Radko & Klement Erich Peter, 2017. "Characterizations of bivariate conic, extreme value, and Archimax copulas," Dependence Modeling, De Gruyter, vol. 5(1), pages 45-58, January.
    14. Yasuo Narukawa & Vicenç Torra & Michio Sugeno, 2016. "Choquet integral with respect to a symmetric fuzzy measure of a function on the real line," Annals of Operations Research, Springer, vol. 244(2), pages 571-581, September.
    15. Kołacz, Adam & Grzegorzewski, Przemysław, 2016. "Measures of dispersion for multidimensional data," European Journal of Operational Research, Elsevier, vol. 251(3), pages 930-937.
    16. Alessio Bonetti & Silvia Bortot & Mario Fedrizzi & Silvio Giove & Ricardo Alberto Marques Pereira & Andrea Molinari, 2011. "Modelling group processes and effort estimation in Project Management using the Choquet integral: an MCDM approach," DISA Working Papers 2011/12, Department of Computer and Management Sciences, University of Trento, Italy, revised Sep 2011.
    17. Marta Cardin, 2023. "Rights Systems and Aggregation Functions on Property Spaces," Mathematics, MDPI, vol. 11(17), pages 1-10, August.
    18. Labreuche, Christophe & Grabisch, Michel, 2018. "Using multiple reference levels in Multi-Criteria Decision aid: The Generalized-Additive Independence model and the Choquet integral approaches," European Journal of Operational Research, Elsevier, vol. 267(2), pages 598-611.
    19. Sascha Kurz & Issofa Moyouwou & Hilaire Touyem, 2021. "Axiomatizations for the Shapley–Shubik power index for games with several levels of approval in the input and output," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 56(3), pages 569-594, April.
    20. Serena Doria, 2022. "Coherent Upper Conditional Previsions Defined through Conditional Aggregation Operators," Mathematics, MDPI, vol. 10(24), pages 1-13, December.

    More about this item

    Statistics

    Access and download statistics

    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:wly:jnljam:v:2012:y:2012:i:1:n:136254. 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: Wiley Content Delivery (email available below). General contact details of provider: https://onlinelibrary.wiley.com/journal/4185 .

    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.