Abstract
We prove that state-of-the-art online asymmetric traveling salesman problem algorithms can successfully be used in real time practical systems, in terms of both solutions quality and computational efficiency. At the same time, we show that such a good behaviour can only be obtained by a careful fine tuning of the algorithms, often clashing with their theoretical analysis.
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Notes
- 1.
The instance has G = 1, following a cluster ordering of the requests and a sparse-first distribution.
References
AD-COM: Project website. https://ad-com.net/. Last access April 2019
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Acknowledgement
This research was partially funded by Regione Lombardia, grant agreement n.E97F17000000009, project AD-COM.
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Barbato, M., Ceselli, A., Mosconi, F. (2019). A Computational Evaluation of Online ATSP Algorithms. In: Paolucci, M., Sciomachen, A., Uberti, P. (eds) Advances in Optimization and Decision Science for Society, Services and Enterprises. AIRO Springer Series, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-34960-8_41
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DOI: https://doi.org/10.1007/978-3-030-34960-8_41
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