• Title of article

    A New Data-driven and Knowledge-driven Multi-criteria Decision-making Method

  • Author/Authors

    Dorfeshan, Y School of Industrial Engineering - College of Engineering - University of Tehran - Tehran, Iran , Tavakkoli-Moghaddam, R School of Industrial Engineering - College of Engineering - University of Tehran - Tehran, Iran , Jolai, F School of Industrial Engineering - College of Engineering - University of Tehran - Tehran, Iran , Mousavi, S.M Department of Industrial Engineering - Faculty of Engineering - Shahed University - Tehran, Iran

  • Pages
    12
  • From page
    543
  • To page
    554
  • Abstract
    Multi-criteria decision-making (MCDM) methods have been received considerable attention for solving problems with a set of alternatives and conflict criteria in the last decade. Previously the MCDM methods have primarily relied on the judgment and knowledge of the experts for making decisions. This paper introduces a new data- and knowledge-driven MCDM method in order to reduce the experts’ assessment dependence. The weight of the criteria is specified using the extended data-driven DEMATEL method. Then, the ranking of alternatives is determined through the knowledge-driven ELECTRE and VIKOR methods. All the proposed methods for weighting and rankings are developed under grey numbers for coping with the uncertainty. Finally, the practicality and applicability of the proposed method are proved by solving an illustrative example.
  • Keywords
    Data-driven and Knowledge-Driven MCDM Methods , DEMATEL , ELECTRE , VIKOR Methods
  • Journal title
    Journal of Artificial Intelligence and Data Mining
  • Serial Year
    2021
  • Record number

    2685983