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
Link To Document :
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