Conflict-Aware Seat Assignment in Classroom Environments

TL;DR

This paper addresses the Student Seat Allocation Problem by proposing a mathematical model and an Iterated Local Search heuristic to optimize classroom seating and reduce conflicts.

Contribution

It introduces a novel problem formulation and demonstrates the effectiveness of a heuristic approach over commercial solvers in complex scenarios.

Findings

ILS outperforms commercial solvers in complex conflict scenarios

The proposed model effectively captures conflict minimization in seating arrangements

ILS is efficient for real and artificial instances with many conflicts

Abstract

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.