The “Soft Computing” journal published the article “Modified fuzzy TOPSIS + TFNs ranking model for candidate selection using the qualifying criteria” co-authored by Vice President of ANAS, Director of the Institute of Information Technology of ANAS, academician Rasim Alguliyev, corresponding member of ANAS, Ramiz Aliguliyev and associate professor, Ph.D. Farhad Yusifov.
Currently, the globalization process significantly impacts not only technological, economical but also social, political and cultural fields. Ongoing social, economic and political processes demonstrate their impacts, and countries are governed by different regimes and government forms. From this standpoint, there is a need for qualified, competent staff for the operation of the regimes and governments. In the article researches, which criteria or factors must be taken into account for selection of competent candidates that are suitable for relevant positions during the election process in contrast to traditional voting. Criteria for candidates’ selection include the adoption of democratic principles, age, education, government agency experience, professional competence, global culture and value acknowledgment, influence in the voting area, leadership skills, activity in social media, etc. In the article implemented multi-criteria evaluation approach for candidate selection. Candidates are ranked based on criteria selected using modified fuzzy TOPSIS and triangular fuzzy numbers ranking methods and different aggregation operators. Candidates are ranked by applying both methods in a numeral experiment, and obtained results are compared. The proposed fuzzy multi-criteria decision-making model allows determining a compromise solution in candidate selection.
Note that the “Soft Computing” journal is indexed in “Web of Science” (IF 2.784), “Compendex”, “Computer Science e Index”, “Current Abstracts”, “ Current Contents ”,“ EBSCO host ”,“ Google Scholar ”,“ SCOPUS ”,“ INSPEC ”,“ IngentConnect ”,“ MetaPress ”,“ Springerlink ”,“ OCLC ” databases.
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