Hybrid Genetic Algorithm using Iterative Deepening Depth-First Search Solution for Timetabling Problem
Timetable scheduling problem in an academic setting is a NP-Hard problem that has room for optimization through machine learning and local search algorithms. Genetic Algorithm, as a meta-heuristic solution, has been utilized to solve this problem. Combined with Iterative Deepening Depth-First Search, a search algorithm utilized to search for solution in a localized problem domain, this paper researches the potential of a hybrid form of genetic algorithm for with the goal to optimize the timetable scheduling problem.