Geração automática de grade horária usando algoritmos genéticos: o caso da Faculdade de Engenharia Elétrica da UFU

• Autor(a) principal: Hamawaki, Cristiane Divina Lemes
• Data de Publicação: 2005
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/14382
• topic: Inteligência artificial; Algoritmos genéticos; Grade horária; Escola; Universidades e Faculdades - Administração - Uberlândia (MG); Artificial intelligence; Genetic algorithm; Timetabling; School; CNPQ::ENGENHARIAS::ENGENHARIA ELETRICA

This study presents the characteristics of using genetic algorithms on the elaboration of Class Schedules for education institutions. The complexity of the problems found to define a good quality solution, in the elaboration of the Class schedule was demonstrated was demonstrated, since there are multiple objectives, multiple restrictions, and a large number of variables to be weighted. Due to the resolution complexity of this kind of problem, it is considered that genetic algorithms are appropriate for use in process automation. Although there are restrictions common to any education institution, there is a large number of restrictions specific for each institution, and this kind of restriction can impose difficulties to the generation process of a general purpose class schedule establishment. The objective of this study was to develop a genetic representation for the problem of creating a class schedule for a given institution, considering resources limitation, based on its information, and using Genetic Algorithms to reach a viable solution, where there was a specific case of staggering: Class Schedule, after the requirements of the education institution were established, FEELT Faculdade de Engenharia Elétrica da UFU Universidade Federal de Uberlândia MG. The techniques jointly used allowed the achievement of a desired solution for the problem, and as far as the application base don a case study, it can be concluded that the approach used has an acceptable result, which can be used in education institutions that have restrictions and problems with faculty acceptance in the relation to the class schedule to be established. As a major contribution of this work, the study and application of evolutive computing techniques (Genetic Algorithms) in conjunction with the restriction problems can be mentioned for the solution of the difficulty in finding schedules for the faculty, when there is a specific case of staggering and the requirements were established by the education institution FEELT Faculdade de Engenharia Elétrica da UFU Universidade ederal de Uberlândia MG.