Otimização da alocação de horários utilizando algoritmos genéticos: um estudo de caso

Abstract

This undergraduate thesis TCC aims to use genetic algorithms to solve the UTP. The justification for choosing this topic lies in the complexity and difficulty of developing suitable schedules in educational institutions, considering constraints such as teacher availability, classroom allocation, and student demands. The methodology employed consists of the application of genetic algorithms, which are computational techniques based on the principles of natural selection and biological evolution. Starting from an initial population of schedules, selection, recombination, and mutation operations are performed to search for optimized solutions over several iterations. The results obtained demonstrate the ability of genetic algorithms to generate feasible solutions for the UTP while satisfying mandatory constraints and optimizing desirable criteria related to the quality of the generated schedules. The evaluation of the solutions was carried out through a fitness function based on hard and soft constraints, allowing the comparison of different selection and recombination strategies. The experiments highlighted the influence of genetic operators on the quality of the solutions found, enabling the generation of more efficient schedules that are better suited to the needs of the educational institution. Thus, the results confirm the feasibility and effectiveness of using genetic algorithms as an approach to solving the UTP.