Keywords
heuristic algorithms
metaheuristics
artificial intelligence
academic planning
Categories
How to Cite
Abstract
Scheduling in universities is a complex problem that requires coordinating multiple factors, such as the availability of professors, classrooms, and courses, in addition to considering student needs. Traditionally, this process is performed manually, which is time-consuming and error-prone. To address this problem, various solutions based on heuristics and meta heuristics have been developed, such as genetic algorithms, simulated annealing, tabu search, and particle swarm optimization.
These approaches optimize resource allocation, reduce scheduling conflicts, and improve academic planning. The application of artificial intelligence and multi-objective optimization techniques represents a promising alternative for efficient scheduling management in educational institutions.
References
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