Abstract
In this paper we present a population based metaheuristic for solving the Minimum Latency Problem, which is the combination of bacterial evolutionary algorithm with local search techniques. The algorithm was tested on TSPLIB benchmark instances, and the results are competitive in terms of accuracy and runtimes with the state-of-the art methods. Except for two instances our algorithm found the best-known solution, and for the biggest tested instance it outperformed the best-known solution. The runtime was on average 30% faster than the most efficient method in the literature.
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Acknowledgements
This research was supported by the National Research, Development and Innovation Office (NKFIH) K108405 and by the EFOP-3.6.2-16-2017-00015 “HU-MATHS-IN-Intensification of the activity of the Hungarian Industrial Innovation Service Network” grant.
Supported by the ÚNKP-17-3 New National Excellence Program of the Ministry of Human Capacities.
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Tüű-Szabó, B., Földesi, P., Kóczy, L.T. (2019). A Population Based Metaheuristic for the Minimum Latency Problem. In: Cornejo, M., Kóczy, L., Medina, J., De Barros Ruano, A. (eds) Trends in Mathematics and Computational Intelligence. Studies in Computational Intelligence, vol 796. Springer, Cham. https://doi.org/10.1007/978-3-030-00485-9_13
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