[go: up one dir, main page]
Skip to main content
Springer Nature Link
Log in

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

  • S.I.: CLAIO 2018
  • Published:
Annals of Operations Research Aims and scope Submit manuscript

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).

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Babin, G., Deneault, S., & Laporte, G. (2007). Improvements to the or-opt heuristic for the symmetric travelling salesman problem. Journal of the Operational Research Society, 58(3), 402–407.

    Article  Google Scholar 

  • Belenguer, J. M., Benavent, E., Labadi, N., Prins, C., & Reghioui, M. (2010). Split-delivery capacitated arc-routing problem: Lower bound and metaheuristic. Transportation Science, 44(2), 206–220.

    Article  Google Scholar 

  • Caggiani, L., & Ottomanelli, M. (2013). A dynamic simulation based model for optimal fleet repositioning in bike-sharing systems. Procedia-Social and Behavioral Sciences, 87, 203–210.

    Article  Google Scholar 

  • Chemla, D., Meunier, F., & Calvo, R. W. (2013). Bike sharing systems: Solving the static rebalancing problem. Discrete Optimization, 10(2), 120–146.

    Article  Google Scholar 

  • Contardo, C., Morency, C., & Rousseau, L. M. (2012). Balancing a dynamic public bike-sharing system (Vol. 4). Canada: Cirrelt Montreal.

    Google Scholar 

  • Dell’Amico, M., Hadjicostantinou, E., Iori, M., & Novellani, S. (2014). The bike sharing rebalancing problem: Mathematical formulations and benchmark instances. Omega, 45, 7–19.

    Article  Google Scholar 

  • Dell’Amico, M., Iori, M., Novellani, S., & Stützle, T. (2016). A destroy and repair algorithm for the bike sharing rebalancing problem. Computers and Operations Research, 71, 149–162.

    Article  Google Scholar 

  • Duhamel, C., Lacomme, P., Quilliot, A., & Toussaint, H. (2011). A multi-start evolutionary local search for the two-dimensional loading capacitated vehicle routing problem. Computers and Operations Research, 38(3), 617–640.

    Article  Google Scholar 

  • Feo, T. A., & Resende, M. G. (1995). Greedy randomized adaptive search procedures. Journal of global optimization, 6(2), 109–133.

    Article  Google Scholar 

  • Forma, I. A., Raviv, T., & Tzur, M. (2015). A 3-step math heuristic for the static repositioning problem in bike-sharing systems. Transportation Research Part B: Methodological, 71, 230–247.

    Article  Google Scholar 

  • Hansen, P., & Mladenović, N. (2001). Variable neighborhood search: Principles and applications. European Journal of Operational Research, 130(3), 449–467.

    Article  Google Scholar 

  • Hansen, P., Mladenović, N., Todosijević, R., & Hanafi, S. (2017). Variable neighborhood search: Basics and variants. EURO Journal on Computational Optimization, 5(3), 423–454.

    Article  Google Scholar 

  • Hernández-Pérez, H., & Salazar-González, J. J. (2004a). A branch-and-cut algorithm for a traveling salesman problem with pickup and delivery. Discrete Applied Mathematics, 145(1), 126–139.

    Article  Google Scholar 

  • Hernández-Pérez, H., & Salazar-González, J. J. (2004b). Heuristics for the one-commodity pickup-and-delivery traveling salesman problem. Transportation Science, 38(2), 245–255.

    Article  Google Scholar 

  • Hernández-Pérez, H., Rodríguez-Martín, I., & Salazar-González, J. J. (2009). A hybrid GRASP/VND heuristic for the one-commodity pickup-and-delivery traveling salesman problem. Computers and Operations Research, 36(5), 1639–1645.

    Article  Google Scholar 

  • Ho, S. C., & Szeto, W. (2014). Solving a static repositioning problem in bike-sharing systems using iterated tabu search. Transportation Research Part E: Logistics and Transportation Review, 69, 180–198.

    Article  Google Scholar 

  • Ho, S. C., & Szeto, W. (2017). A hybrid large neighborhood search for the static multi-vehicle bike-repositioning problem. Transportation Research Part B: Methodological, 95, 340–363.

    Article  Google Scholar 

  • Kloimüllner, C., Papazek, P., Hu, B. & Raidl, G. R. (2014). Balancing bicycle sharing systems: An approach for the dynamic case. In European conference on evolutionary computation in combinatorial optimization (pp. 73–84). Berlin: Springer.

  • Legros, B. (2019). Dynamic repositioning strategy in a bike-sharing system; how to prioritize and how to rebalance a bike station. European Journal of Operational Research, 272(2), 740–753.

    Article  Google Scholar 

  • Lin, S. (1965). Computer solutions of the traveling salesman problem. Bell System Technical Journal, 44(10), 2245–2269.

    Article  Google Scholar 

  • Lourenço, H. R., Martin, O. C., & Stützle, T. (2003). Iterated local search. In F. Glover & G. Kochenberger (Eds.), Handbook of metaheuristics (pp. 320–353). Berlin: Springer.

    Chapter  Google Scholar 

  • Miller, C. E., Tucker, A. W., & Zemlin, R. A. (1960). Integer programming formulation of traveling salesman problems. Journal of the ACM (JACM), 7(4), 326–329.

    Article  Google Scholar 

  • Mladenović, N., Urošević, D., Ilić, A., et al. (2012). A general variable neighborhood search for the one-commodity pickup-and-delivery travelling salesman problem. European Journal of Operational Research, 220(1), 270–285.

    Article  Google Scholar 

  • Or, I. (1976). Traveling salesman-type combinatorial problems and their relation to the logistics of regional blood banking. Ph.D. Thesis, Department of Industrial Engineering and Management Science, Northwestern University.

  • Palacio, J. D. & Rivera, J. C. (2019). Mixed-integer linear programming models for one-commodity pickup and delivery traveling salesman problems. In Workshop on engineering applications (pp. 735–751). Springer.

  • Prins, C. (2009). A GRASP \(\times \) evolutionary local search hybrid for the vehicle routing problem. In Bio-inspired algorithms for the vehicle routing problem (pp. 35–53). Springer.

  • Raviv, T., Tzur, M., & Forma, I. A. (2013). Static repositioning in a bike-sharing system: Models and solution approaches. EURO Journal on Transportation and Logistics, 2(3), 187–229.

    Article  Google Scholar 

  • Resende, M. G., & Ribeiro, C. C. (2016). Optimization by GRASP: Greedy randomized adaptive search procedures (1st ed.). New York: Springer.

    Book  Google Scholar 

  • Rivera, J. C., Afsar, H. M. & Prins, C. (2013). Multistart evolutionary local search for a disaster relief problem. In International conference on artificial evolution (evolution artificielle) (pp. 129–141). Springer.

  • Shui, C., & Szeto, W. (2018). Dynamic green bike repositioning problem: a hybrid rolling horizon artificial bee colony algorithm approach. Transportation Research Part D: Transport and Environment, 60, 119–136.

    Article  Google Scholar 

  • Szeto, W., Liu, Y., & Ho, S. C. (2016). Chemical reaction optimization for solving a static bike repositioning problem. Transportation Research Part D: Transport and Environment, 47, 104–135.

    Article  Google Scholar 

  • Villegas, J. G., Prins, C., Prodhon, C., Medaglia, A. L., & Velasco, N. (2010). GRASP/VND and multi-start evolutionary local search for the single truck and trailer routing problem with satellite depots. Engineering Applications of Artificial Intelligence, 23(5), 780–794.

    Article  Google Scholar 

  • Wolf, S. & Merz, P. (2007). Evolutionary local search for the super-peer selection problem and the p-hub median problem. In International workshop on hybrid metaheuristics (pp. 1–15). Springer.

  • Zhang, D., Yu, C., Desai, J., Lau, H., & Srivathsan, S. (2017). A time-space network flow approach to dynamic repositioning in bicycle sharing systems. Transportation Research Part B: Methodological, 103, 188–207.

    Article  Google Scholar 

  • Zhao, F., Li, S., Sun, J., & Mei, D. (2009). Genetic algorithm for the one-commodity pickup-and-delivery traveling salesman problem. Computers and Industrial Engineering, 56(4), 1642–1648.

    Article  Google Scholar 

Download references

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.

Author information

Authors and Affiliations

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

    Juan D. Palacio & Juan Carlos Rivera

Authors
  1. Juan D. Palacio
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan Carlos Rivera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Juan D. Palacio.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

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

Download citation

  • Accepted:

  • Published:

  • Issue Date:

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

Keywords

Search

Navigation