The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars
Seminars are offered to students for education in various disciplines. The seminars may be limited in terms of the maximum number of participants, e.g., to have lively interactions. Due to capacity limitations, those seminars are often offered several times to serve the students' demands. Still...
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| Format: | Article |
| Language: | English |
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Wrocław University of Science and Technology
2023-01-01
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| Series: | Operations Research and Decisions |
| Online Access: | https://ord.pwr.edu.pl/assets/papers_archive/ord2023vol33no3_1.pdf |
| _version_ | 1827793019986771968 |
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| author | Tobias Hoßfeld |
| author_facet | Tobias Hoßfeld |
| author_sort | Tobias Hoßfeld |
| collection | DOAJ |
| description | Seminars are offered to students for education in various disciplines. The seminars may be limited in terms of the maximum number of participants, e.g., to have lively interactions. Due to capacity limitations, those seminars are often offered several times to serve the students' demands. Still, some seminars are more popular than others and it may not be possible to grant access to all interested students due to capacity limitations. In this paper, a simple, but efficient random selection using key objectives (SEKO) assignment strategy is proposed which achieves the following goals: (i) efficiency by utilizing all available seminar places, (ii) satisfying all students by trying to assign at least one seminar to each student, and (iii) fairness by considering the number of assigned seminars per student. We formulate various theoretical optimization models using integer linear programming (ILP) and compare their solutions to the SEKO assignment based on a real-world data set. The real-world data set is also used as the basis for generating large data sets to investigate the scalability in terms of demand and number of seminars. Furthermore, the first-in first-out (FIFO) assignment, as a typical implementation of fair assignments in practice, is compared to SEKO in terms of utilization and fairness. The results show that the FIFO assignment suffers in real world situations regarding fairness, while the SEKO assignment is close to the optimum and scales regarding computational time in contrast to the ILP. (original abstract) |
| first_indexed | 2024-03-11T18:12:33Z |
| format | Article |
| id | doaj.art-c26a04c0020542548d85f1452f549751 |
| institution | Directory Open Access Journal |
| issn | 2081-8858 2391-6060 |
| language | English |
| last_indexed | 2024-03-11T18:12:33Z |
| publishDate | 2023-01-01 |
| publisher | Wrocław University of Science and Technology |
| record_format | Article |
| series | Operations Research and Decisions |
| spelling | doaj.art-c26a04c0020542548d85f1452f5497512023-10-16T11:51:02ZengWrocław University of Science and TechnologyOperations Research and Decisions2081-88582391-60602023-01-01vol. 33no. 3127171673491The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple SeminarsTobias Hoßfeld0University of Würzburg, GermanySeminars are offered to students for education in various disciplines. The seminars may be limited in terms of the maximum number of participants, e.g., to have lively interactions. Due to capacity limitations, those seminars are often offered several times to serve the students' demands. Still, some seminars are more popular than others and it may not be possible to grant access to all interested students due to capacity limitations. In this paper, a simple, but efficient random selection using key objectives (SEKO) assignment strategy is proposed which achieves the following goals: (i) efficiency by utilizing all available seminar places, (ii) satisfying all students by trying to assign at least one seminar to each student, and (iii) fairness by considering the number of assigned seminars per student. We formulate various theoretical optimization models using integer linear programming (ILP) and compare their solutions to the SEKO assignment based on a real-world data set. The real-world data set is also used as the basis for generating large data sets to investigate the scalability in terms of demand and number of seminars. Furthermore, the first-in first-out (FIFO) assignment, as a typical implementation of fair assignments in practice, is compared to SEKO in terms of utilization and fairness. The results show that the FIFO assignment suffers in real world situations regarding fairness, while the SEKO assignment is close to the optimum and scales regarding computational time in contrast to the ILP. (original abstract)https://ord.pwr.edu.pl/assets/papers_archive/ord2023vol33no3_1.pdf |
| spellingShingle | Tobias Hoßfeld The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars Operations Research and Decisions |
| title | The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars |
| title_full | The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars |
| title_fullStr | The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars |
| title_full_unstemmed | The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars |
| title_short | The SEKO Assignment. Efficient and Fair Assignment of Students to Multiple Seminars |
| title_sort | seko assignment efficient and fair assignment of students to multiple seminars |
| url | https://ord.pwr.edu.pl/assets/papers_archive/ord2023vol33no3_1.pdf |
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