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PCGLNS: A Heuristic Solver for the Precedence Constrained Generalized Traveling Salesman Problem

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Optimization and Applications (OPTIMA 2020)

Abstract

The Precedence Constrained Generalized Traveling Salesman Problem (PCGTSP) is a specialized version of the well-known Generalized Traveling Salesman Problem (GTSP) having a lot of valuable applications in operations research. Despite the practical significance, results in the field of design, implementation, and numerical evaluation the algorithms for this problem remain still rare. In this paper, to the best of our knowledge, we propose the first heuristic solver for this problem augmented by numerical evaluation results of its performance against the public test instances library PCGTSPLIB. Our algorithm is an extension of the recent Large Neighborhood Search (GLNS) heuristic GTSP solver designed to take into account additional precedence constraints. Similarly to GLNS, the source code of all our algorithms is open, and the executables are freely accessible, which ensures the reproducibility of the reported numerical results.

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Notes

  1. 1.

    Indeed, in the case of the linear order, the instance becomes trivial.

  2. 2.

    To the best of our knowledge.

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Acknowledgements

This research was performed as part of research conducted in the Ural Mathematical Center and funded by the Russian Foundation for Basic Research, grants no. 19-07-01243 and 20-08-00873.

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Correspondence to Michael Khachay , Andrei Kudriavtsev or Alexander Petunin .

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Khachay, M., Kudriavtsev, A., Petunin, A. (2020). PCGLNS: A Heuristic Solver for the Precedence Constrained Generalized Traveling Salesman Problem. In: Olenev, N., Evtushenko, Y., Khachay, M., Malkova, V. (eds) Optimization and Applications. OPTIMA 2020. Lecture Notes in Computer Science(), vol 12422. Springer, Cham. https://doi.org/10.1007/978-3-030-62867-3_15

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