Abstract
This paper deals with the Tool Switching Problem (ToSP), a well-known problem in operations research. The ToSP involves determining a job sequence and the tools to be loaded on a machine with the goal of minimizing the total number of tool switches. This problem has been tackled by a number of algorithmic approaches in recent years. Here, we propose a memetic algorithm that combines a problem-specific permutational genetic algorithm with a hill-climbing procedure. It is shown that this combined approach outperforms each of the individual algorithms, as well as an ad-hoc beam search heuristic defined in the literature for this problem.
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Amaya, J.E., Cotta, C., Fernández, A.J. (2008). A Memetic Algorithm for the Tool Switching Problem. In: Blesa, M.J., et al. Hybrid Metaheuristics. HM 2008. Lecture Notes in Computer Science, vol 5296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88439-2_14
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DOI: https://doi.org/10.1007/978-3-540-88439-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-88438-5
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