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This paper introduces the Student Seat Allocation Problem (SSAP) to optimize classroom seating arrangements by minimizing interpersonal conflicts. They formulate a mathematical model for SSAP and develop an Iterated Local Search (ILS) heuristic to solve it. Experimental results show that ILS outperforms a commercial solver, especially in complex scenarios with a high number of conflicts.
Optimizing classroom seating arrangements to minimize student conflicts can be effectively achieved using an Iterated Local Search heuristic, outperforming commercial solvers in complex scenarios.
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.