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.
| Original language | English |
|---|---|
| Pages (from-to) | 528-540 |
| Number of pages | 13 |
| Journal | Journal of the Operational Research Society |
| Volume | 69 |
| Issue number | 4 |
| DOIs | |
| State | Published - 3 Apr 2018 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 4 Quality Education
Keywords
- Decision analysis
- education
- ELECTRE
- practice of OR
- TOPSIS
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