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A multi-start evolutionary local search for the one-commodity pickup and delivery traveling salesman problem

  • S.I.: CLAIO 2018
  • Published:
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Abstract

This article addresses the one-commodity pickup and delivery traveling salesman problem (1-PDTSP), which is a generalization of the well-known traveling salesman problem. The 1-PDTSP aims to find a Hamiltonian tour in which a set of supply points (pickup locations), demand points (delivery locations) are visited and, the total traveled distance is minimized. We propose a hybrid metaheuristic based on multi-start evolutionary local search and variable neighborhood descent to solve the 1-PDTSP. To test the performance of our algorithm, we solve instances with up to 500 nodes available in the literature and we demonstrate that our approach is able to provide competitive results when comparing to other existing strategies. Since a direct application of the 1-PDTSP arises as the bicycle repositioning problem, we also use our metaheuristic algorithm to solve a set of real-case instances based on EnCicla, the bicycle sharing system in the Aburrá Valley (Antioquia, Colombia).

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Acknowledgements

The present research work has been supported by Universidad EAFIT. The authors would like to thank Subdirección de Movilidad department from Área metropolitana del Valle de Aburrá, for providing us with information for the instances described in Sect. 5.1.2.

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  1. Mathematical Modeling Research Group. Mathematical Sciences Department, School of Sciences, Universidad EAFIT, Medellín, Colombia

    Juan D. Palacio & Juan Carlos Rivera

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  1. Juan D. Palacio
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  2. Juan Carlos Rivera
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Correspondence to Juan D. Palacio.

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Palacio, J.D., Rivera, J.C. A multi-start evolutionary local search for the one-commodity pickup and delivery traveling salesman problem. Ann Oper Res 316, 979–1011 (2022). https://doi.org/10.1007/s10479-020-03789-0

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  • DOI: https://doi.org/10.1007/s10479-020-03789-0

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