OPTIMIZATION MODELS FOR THE EFFICIENT ALLOCATION OF ACADEMIC SPACES: THE CASE OF A HIGHER EDUCATION INSTITUTION

The objective of this study is to propose a model for optimizing classroom physical space on the campus of a Federal Higher Education Institution (IFES). Regarding the methodology, data collection sources used to propose the models included observations, unstructured and informal interviews, and pertinent documents obtained from the IFES Information and Communication Technology Center (CTIC) for the 2023-2021 semester. Mathematical programming was used with the support of GAMS (General Algebraic Modeling System) software, and mathematical models were developed using Binary Linear Programming and adjusted for different scenarios, always aiming to minimize the number of classrooms required. Parameters related to curricular components, available classrooms, days of the week, available times during the critical period (between 7:00 PM and 10:30 PM), and the weekly frequency of classes in the curricular component were considered. The results indicated that scenario 1 is the most flexible and required the use of 34 classrooms. Despite using all available classrooms, no bottlenecks were identified on any day of the week, which is an improvement over the actual situation. In 2023-1, bottlenecks in classroom use occurred on Tuesdays. In Scenario 2, all the conditions established in Scenario 1 were maintained, except that courses were grouped in nearby classrooms. This increased the demand to 37 classrooms. It is important to note that, in this scenario, the same course may still be offered in different classrooms if it occurs more than once a week. In Scenario 3, in addition to grouping courses, courses were kept in the same classroom when they occur more than once a week. This scenario also requires the same 37 classrooms used in Scenario 2. In Scenario 4, faculty allocation was considered as in 2023-1, resulting in the need for 37 classrooms. In Scenario 5, faculty allocation was maintained, but specific classrooms were not required for each course, resulting in the need for 35 classrooms. In the final scenario, the previously established time slots were allocated and the model was tested with two configurations: one with dedicated course rooms and the other without. This resulted in 38 and 37 rooms, respectively. It is clear here that grouping courses in nearby rooms always increases the need for rooms. Thus, the results show variations in room demand depending on the imposed constraints, highlighting the importance of a flexible and collaborative approach among stakeholders to optimize the use of academic space. This research highlights the complexity and importance of physical space, influenced by various factors, and the need for effective solutions for distributing resources and people within classrooms.