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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2026
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2605.04235 |
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| _version_ | 1866911650096873472 |
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| author | Charytitsch, Bruna Cristina Braga Nascimento, Mariá Cristina Vasconcelos |
| author_facet | Charytitsch, Bruna Cristina Braga Nascimento, Mariá Cristina Vasconcelos |
| contents | Classroom dynamics depend on various elements that influence teaching performance and learning activities. A key challenge is to determine the most effective seating plan, where students will seat in a specific classroom setting to achieve the best learning environment. This paper introduces the Student Seat Allocation Problem (SSAP) for strategically organizing student seating in traditional classrooms to minimize interpersonal conflicts. We propose a mathematical model and an Iterated Local Search (ILS) heuristic to solve the SSAP. Computational experiments demonstrated that ILS outperformed in more complex scenarios when compared to the results obtained by a commercial solver on the introduced mathematical model. ILS was particularly efficient in real and artificial instances that exhibited a higher number of conflicts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_04235 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Conflict-Aware Seat Assignment in Classroom Environments Charytitsch, Bruna Cristina Braga Nascimento, Mariá Cristina Vasconcelos Combinatorics Computers and Society Optimization and Control Classroom dynamics depend on various elements that influence teaching performance and learning activities. A key challenge is to determine the most effective seating plan, where students will seat in a specific classroom setting to achieve the best learning environment. This paper introduces the Student Seat Allocation Problem (SSAP) for strategically organizing student seating in traditional classrooms to minimize interpersonal conflicts. We propose a mathematical model and an Iterated Local Search (ILS) heuristic to solve the SSAP. Computational experiments demonstrated that ILS outperformed in more complex scenarios when compared to the results obtained by a commercial solver on the introduced mathematical model. ILS was particularly efficient in real and artificial instances that exhibited a higher number of conflicts. |
| title | Conflict-Aware Seat Assignment in Classroom Environments |
| topic | Combinatorics Computers and Society Optimization and Control |
| url | https://arxiv.org/abs/2605.04235 |