Abstract
It is well known that domain-specific heuristics can produce good-quality solutions for timetabling problems in a short amount of time. However, they often lack the ability to do any thorough optimisation. In this paper we will study the effects of applying local search techniques to improve good-quality initial solutions generated using a heuristic construction method. While the same rules should apply to any heuristic construction, we use here an adaptive approach to timetabling problems. The focus of the experiments is how parameters to the local search methods affect quality when started on already good solutions. We present experimental results which show that this combined approach produces the best published results on several benchmark problems and we briefly discuss the implications for future work in the area.
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Burke, E.K., Newall, J.P. (2003). Enhancing Timetable Solutions with Local Search Methods. In: Burke, E., De Causmaecker, P. (eds) Practice and Theory of Automated Timetabling IV. PATAT 2002. Lecture Notes in Computer Science, vol 2740. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45157-0_13
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DOI: https://doi.org/10.1007/978-3-540-45157-0_13
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