Abstract
The paper provides a study of the use of hyper-heuristics on the movie scene scheduling problem. In particular, the paper extends the definition of the movie scene scheduling problem to include a new method of calculating the solution quality. The study is also a novel application of hyper-heuristics to the movie scene scheduling problem and demonstrates one potential method for using hyper-heuristics as a solution method for the given problem. This includes the development of new low-level heuristics for the problem that are presented as well. The study showed that hyper-heuristics could be applied to the problem doing better than a random approach but that work would need to be done on improving the low-level perturbative heuristics. The study also showed that the new formulation would be tenable as a problem definition with little change to the underlying problem itself.
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Acknowledgements
This work was funded as part of the Multichoice Research Chair in Machine Learning at the University of Pretoria, South Africa. This work is based on the research supported wholly/in part by the National Research Foundation of South Africa (Grant Numbers 46712). Opinions expressed and conclusions arrived at, are those of the author and are not necessarily to be attributed to the NRF.
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Singh, E., Pillay, N. (2021). Ant-Based Hyper-Heuristics for the Movie Scene Scheduling Problem. In: Rutkowski, L., Scherer, R., Korytkowski, M., Pedrycz, W., Tadeusiewicz, R., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2021. Lecture Notes in Computer Science(), vol 12855. Springer, Cham. https://doi.org/10.1007/978-3-030-87897-9_31
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DOI: https://doi.org/10.1007/978-3-030-87897-9_31
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