Abstract
Student selection is a complex decision-making process, in which several criteria need to be considered simultaneously. In this paper, we address this problem for a Brazilian university that has created an interdisciplinary degree in which several intermediate selection processes are required during the course, defining the final title degree. The university is currently using an aggregated score based on the performance of a student in the course. However, this method is facing difficulties in selecting the best students, because deficiencies in the way transferred, dropped and quit course credits are accounted for. As a possible alternative for the current method, we developed a hybrid ranking algorithm, called ELECTRE–TOPSIS (E–T). This method combines elements of the ELECTRE family and TOPSIS, two well-known multi-attribute analysis tools, to rank students based on objective criteria. Computational experiments and a case study were conducted to evaluate E–T. The results show that our approach provides quite competitive rankings in comparison with similar methods, through simultaneously eliminating ranking reversal and better balancing the formation time and the academic performance of the evaluated students.
Acknowledgements
The authors thank the two anonymous referees for their comments that greatly improved the quality of the paper. This research work was partially founded by CNPq, Brazil, grants 301453/2013-6 and 304536/2016-4, and CAPES, Brazil.
Notes
Please note this paper has been re-typeset by Taylor & Francis from the manuscript originally provided to the previous publisher.