@article { author = {Dorfeshan, Y. and Tavakkoli-Moghaddam, R. and Jolai, F. and Mousavi, S.M.}, title = {A New Data-driven and Knowledge-driven Multi-criteria Decision-making Method}, journal = {Journal of AI and Data Mining}, volume = {9}, number = {4}, pages = {543-554}, year = {2021}, publisher = {Shahrood University of Technology}, issn = {2322-5211}, eissn = {2322-4444}, doi = {10.22044/jadm.2021.10803.2218}, 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, MCDM methods have primarily relied on the judgment and knowledge of experts for making decisions. This paper introduces a new data- and knowledge-driven MCDM method to reduce experts’ assessment dependence. The weight of the criteria is specified by using the extended data-driven DEMATEL method. Then, the ranking of alternatives is determined through knowledge-driven ELECTRE and VIKOR methods. All 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 MCDM method,Knowledge-driven MCDM method,DEMATEL,ELECTRE,VIKOR}, url = {https://jad.shahroodut.ac.ir/article_2243.html}, eprint = {https://jad.shahroodut.ac.ir/article_2243_eb8c998bfe258804e28e6f0d037b32f1.pdf} }