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The Discrete Bacterial Memetic Evolutionary Algorithm for Solving the One-Commodity Pickup-and-Delivery Traveling Salesman Problem

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Book cover Computational Intelligence and Mathematics for Tackling Complex Problems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 819))

Abstract

In this paper we propose a population based memetic algorithm, the Discrete Bacterial Memetic Evolutionary Algorithm for solving the one-commodity Pickup-and-Delivery Traveling Salesman Problem. The algorithm was tested on benchmark instances up to 100 nodes, and the results were compared with the state-of-the art methods in the literature. For all instances the DBMEA found optimal or close-optimal solutions.

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Acknowledgements

The research presented in this paper was funded by the Higher Education Institutional Excellence Program.

This research was supported by the National Research, Development and Innovation Office (NKFIH) K124055.

Supported by the ÚNKP-17-3 New National Excellence Program of the Ministry of Human Capacities.

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Correspondence to Boldizsár Tüű-Szabó .

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Tüű-Szabó, B., Földesi, P., Kóczy, L.T. (2020). The Discrete Bacterial Memetic Evolutionary Algorithm for Solving the One-Commodity Pickup-and-Delivery Traveling Salesman Problem. In: Kóczy, L., Medina-Moreno, J., Ramírez-Poussa, E., Šostak, A. (eds) Computational Intelligence and Mathematics for Tackling Complex Problems. Studies in Computational Intelligence, vol 819. Springer, Cham. https://doi.org/10.1007/978-3-030-16024-1_3

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