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Weight Vector Generation in Multi-Criteria Decision-Making with Basic Uncertain Information

Author

Listed:
  • Ya-Qiang Xu

    (Department of Engineering Management, School of Civil Engineering, Wuhan University, Wuhan 430072, China)

  • Le-Sheng Jin

    (Business School, Nanjing Normal University, Nanjing 210023, China)

  • Zhen-Song Chen

    (Department of Engineering Management, School of Civil Engineering, Wuhan University, Wuhan 430072, China)

  • Ronald R. Yager

    (Machine Intelligence Institute, Iona College, New Rochelle, NY 10801, USA)

  • Jana Špirková

    (Faculty of Economics, Matej Bel University, Tajovského 10, Sk-975 90 Banská Bystrica, Slovakia)

  • Martin Kalina

    (Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, Sk-810 05 Bratislava, Slovakia)

  • Surajit Borkotokey

    (Department of Mathematics, Dibrugarh University, Dibrugarh 786004, India)

Abstract

This paper elaborates the different methods to generate normalized weight vector in multi-criteria decision-making where the given information of both criteria and inputs are uncertain and can be expressed by basic uncertain information. Some general weight allocation paradigms are proposed in view of their convenience in expression. In multi-criteria decision-making, the given importance for each considered criterion may have different extents of uncertainty. Accordingly, we propose some special induced weight-allocation methods. The inputs can be also associated with varying uncertainty extents, and then we develop several induced weight-generation methods for consideration. In addition, we present some suggested and prescriptive weight allocation rules and analyze their reasonability.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:4:p:572-:d:747720
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    References listed on IDEAS

    as
    1. Thomas L. Saaty, 1986. "Axiomatic Foundation of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 32(7), pages 841-855, July.
    2. Michel Grabisch & Jean-Luc Marichal & Radko Mesiar & Endre Pap, 2009. "Aggregation functions," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00445120, HAL.
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