Minimizando os custos energéticos de alocação de aulas a salas: o caso de uma instituição federal de ensino

• Autor(a) principal: Alves, Raphael Medeiros
• Data de Publicação: 2019
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFPB
• Texto Completo: https://repositorio.ufpb.br/jspui/handle/123456789/19513
• topic: Problemas de alocação de aulas a salas; Programação Linear Inteira; Custo energético; Classroom assignment problem; Integer programming; Energy cost; Sala de aula - alocação; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

This work deals with the classroom assignment problem (CAP) in the context of a largescale federal educational institution. In practice, such problem must be solved at the beginning of every semester. Currently, the CAP arising in the referred institution is solved manually, which is not only an arduous task, but also very time consuming, often leading to ine cient solutions. By analyzing the manual solution through the energy cost perspective, it is possible to verify that there are nancial losses. For example, it is not interesting to allocate classes with few students to rooms with large capacities, which in turn tend to have higher energy costs. In addition, an inadequate solution can generate a false perception of room shortages, thus inaccurately implying that new rooms must be built to properly accommodate all classes. The objective of this study is to minimize the energy cost associated with the usage of the locations where classes can take place, in this case regular classrooms and computer labs, while meeting the requirements speci ed by the institution. To solve di erent versions of the problem, scenarios of mathematical formulations based on integer linear programming were proposed. The models developed were tested on real two campus instances involving up to 3046 classes and 97 locations. All of the proposed formulation scenarios were capable to acachieving a signi cant reduction in energy costs compared to the manual solution, with up to 30% energy savings. Among these formulations, the minimization of the number of class locations was also a purpose of this study, where a reduction of 97 to 55 classrooms was obtained with the most recent instance of the case studied.