Timetabling tasks form a widely studied type of resource scheduling problem, with important real-world applications in schools, universities and other educational settings. In this work, we focus on post-enrollment course timetabling, the problem that was covered by Track 2 of the recent 2nd International Timetabling Competition (ITC2007). Following an approach that makes strong use of automated exploration of a large design space of modular and highly parameterised stochastic local search algorithms for this problem, we produced a solver that placed third in Track 2 of ITC2007. In subsequent work, we further improved both the solver framework and the automated algorithm design procedure, and obtained a solver that achieves consistently better performance than the top-ranked solver from the competition and represents a substantial improvement in the state of the art for post-enrollment course timetabling.
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