IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i18p2944-d1483062.html
   My bibliography  Save this article

A Method to Handle the Missing Values in Multi-Criteria Sorting Problems Based on Dominance Rough Sets

Author

Listed:
  • Ahmet Topal

    (Department of Mathematics Engineering, Istanbul Technical University, Sariyer, 34469 Istanbul, Türkiye
    Department of Mathematics Engineering, Yildiz Technical University, Esenler, 34220 Istanbul, Türkiye)

  • Nilgun Guler Bayazit

    (Department of Mathematics Engineering, Yildiz Technical University, Esenler, 34220 Istanbul, Türkiye)

  • Yasemen Ucan

    (Department of Mathematics Engineering, Yildiz Technical University, Esenler, 34220 Istanbul, Türkiye)

Abstract

The handling of missing attribute values remains a challenging and problematic issue in data analysis. Imputation techniques are key procedures used to deal with missing attribute values. However, although these methods are widely used, they cause data bias. Rough set theory, a unique mathematical tool for decision making under uncertainty, overcomes this problem by properly adjusting the relationships. Rough sets are often preferred in both classification and sorting problems. The aim of sorting problems is to sort the objects in the decision table (DT) from best to worst and/or to select the best one. For this purpose, it is necessary to obtain a pairwise comparison table (PCT) from the DT. However, in the presence of missing values, the transformation from DT to PCT is not feasible because there are no ranking methods in the literature for sorting problems based on rough sets. To address this limitation, this paper presents a way to transform from DT to PCT and introduces a generalization of the relation belonging to the “do not care” type of missing values in the dominance-based rough set approach (DRSA) to the decision support tool jRank. We also adapted the DomLem algorithm to enable it to work in PCT with missing values. We applied our method step by step to a decision table with 11 objects and investigated the effect of missing values. The experimental results showed that our proposed approach captures the semantics of ‘do not care’ type missing values.

Suggested Citation

  • Ahmet Topal & Nilgun Guler Bayazit & Yasemen Ucan, 2024. "A Method to Handle the Missing Values in Multi-Criteria Sorting Problems Based on Dominance Rough Sets," Mathematics, MDPI, vol. 12(18), pages 1-18, September.
  • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2944-:d:1483062
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/18/2944/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/12/18/2944/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Greco, Salvatore & Matarazzo, Benedetto & Slowinski, Roman, 2001. "Rough sets theory for multicriteria decision analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 1-47, February.
    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. Wen-Min Lu & Qian Long Kweh & Chung-Wei Wang, 2021. "Integration and application of rough sets and data envelopment analysis for assessments of the investment trusts industry," Annals of Operations Research, Springer, vol. 296(1), pages 163-194, January.
    2. Pang, Jifang & Liang, Jiye, 2012. "Evaluation of the results of multi-attribute group decision-making with linguistic information," Omega, Elsevier, vol. 40(3), pages 294-301.
    3. Eduardo Fernández & José Rui Figueira & Jorge Navarro, 2023. "A theoretical look at ordinal classification methods based on comparing actions with limiting boundaries between adjacent classes," Annals of Operations Research, Springer, vol. 325(2), pages 819-843, June.
    4. Doumpos, M. & Marinakis, Y. & Marinaki, M. & Zopounidis, C., 2009. "An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method," European Journal of Operational Research, Elsevier, vol. 199(2), pages 496-505, December.
    5. Skorupski, Jacek & Uchroński, Piotr, 2017. "A fuzzy model for evaluating metal detection equipment at airport security screening checkpoints," International Journal of Critical Infrastructure Protection, Elsevier, vol. 16(C), pages 39-48.
    6. Bouyssou, Denis & Marchant, Thierry, 2007. "An axiomatic approach to noncompensatory sorting methods in MCDM, II: More than two categories," European Journal of Operational Research, Elsevier, vol. 178(1), pages 246-276, April.
    7. repec:dau:papers:123456789/4080 is not listed on IDEAS
    8. Becchio, Cristina & Bottero, Marta Carla & Corgnati, Stefano Paolo & Dell’Anna, Federico, 2018. "Decision making for sustainable urban energy planning: an integrated evaluation framework of alternative solutions for a NZED (Net Zero-Energy District) in Turin," Land Use Policy, Elsevier, vol. 78(C), pages 803-817.
    9. Fernandez, Eduardo & Navarro, Jorge & Bernal, Sergio, 2010. "Handling multicriteria preferences in cluster analysis," European Journal of Operational Research, Elsevier, vol. 202(3), pages 819-827, May.
    10. Pawel Lezanski & Maria Pilacinska, 2018. "The dominance-based rough set approach to cylindrical plunge grinding process diagnosis," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 989-1004, June.
    11. Tsoukias, Alexis, 2008. "From decision theory to decision aiding methodology," European Journal of Operational Research, Elsevier, vol. 187(1), pages 138-161, May.
    12. Choudhary, Devendra & Shankar, Ravi, 2012. "An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India," Energy, Elsevier, vol. 42(1), pages 510-521.
    13. McKenna, R. & Bertsch, V. & Mainzer, K. & Fichtner, W., 2018. "Combining local preferences with multi-criteria decision analysis and linear optimization to develop feasible energy concepts in small communities," European Journal of Operational Research, Elsevier, vol. 268(3), pages 1092-1110.
    14. García Cáceres, Rafael Guillermo & Aráoz Durand, Julián Arturo & Gómez, Fernando Palacios, 2009. "Integral analysis method - IAM," European Journal of Operational Research, Elsevier, vol. 192(3), pages 891-903, February.
    15. Bouyssou, Denis & Pirlot, Marc, 2009. "An axiomatic analysis of concordance-discordance relations," European Journal of Operational Research, Elsevier, vol. 199(2), pages 468-477, December.
    16. Azam, Nouman & Zhang, Yan & Yao, JingTao, 2017. "Evaluation functions and decision conditions of three-way decisions with game-theoretic rough sets," European Journal of Operational Research, Elsevier, vol. 261(2), pages 704-714.
    17. Nikolaos Argyris & Alec Morton & José Rui Figueira, 2014. "CUT: A Multicriteria Approach for Concavifiable Preferences," Operations Research, INFORMS, vol. 62(3), pages 633-642, June.
    18. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge & Solares, Efrain, 2022. "Handling imperfect information in multiple criteria decision-making through a comprehensive interval outranking approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    19. Beynon, Malcolm J., 2005. "A novel technique of object ranking and classification under ignorance: An application to the corporate failure risk problem," European Journal of Operational Research, Elsevier, vol. 167(2), pages 493-517, December.
    20. Sung-Shun Weng & Yang Liu & Juan Dai & Yen-Ching Chuang, 2020. "A Novel Improvement Strategy of Competency for Education for Sustainable Development (ESD) of University Teachers Based on Data Mining," Sustainability, MDPI, vol. 12(7), pages 1-18, March.
    21. Kadziński, Miłosz & Wójcik, Michał & Ciomek, Krzysztof, 2022. "Review and experimental comparison of ranking and choice procedures for constructing a univocal recommendation in a preference disaggregation setting," Omega, Elsevier, vol. 113(C).

    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:gam:jmathe:v:12:y:2024:i:18:p:2944-:d:1483062. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.