IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v32y2016i4d10.1007_s10878-015-9931-5.html
   My bibliography  Save this article

Approximation schemes for Euclidean vehicle routing problems with time windows

Author

Listed:
  • Liang Song

    (Harbin Institute of Technology Shenzhen Graduate School
    Shenzhen Key Laboratory of Internet Information Collaboration)

  • Hejiao Huang

    (Harbin Institute of Technology Shenzhen Graduate School
    Shenzhen Key Laboratory of Internet Information Collaboration)

  • Hongwei Du

    (Harbin Institute of Technology Shenzhen Graduate School
    Shenzhen Key Laboratory of Internet Information Collaboration)

Abstract

The vehicle routing problem with time windows (VRPTW) is a variant of the classical vehicle routing problem. The paper considers two dimensional and one dimensional VRPTW, in which each demand must be serviced within the time window which is designated by its customer. In the two dimensional problem, each customer has the same unit demand. The paper gives a quasi-polynomial time approximation scheme and an asymptotic polynomial time approximation scheme for the two dimensional and one dimensional problems under the Euclidean setting, respectively. With reasonable vehicle speed requirements, our algorithms could generate the solutions whose the total route length is $$(1 + O(\varepsilon ))$$ ( 1 + O ( ε ) ) times of that of the optimum solutions.

Suggested Citation

  • Liang Song & Hejiao Huang & Hongwei Du, 2016. "Approximation schemes for Euclidean vehicle routing problems with time windows," Journal of Combinatorial Optimization, Springer, vol. 32(4), pages 1217-1231, November.
  • Handle: RePEc:spr:jcomop:v:32:y:2016:i:4:d:10.1007_s10878-015-9931-5
    DOI: 10.1007/s10878-015-9931-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-015-9931-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10878-015-9931-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. G. B. Dantzig & J. H. Ramser, 1959. "The Truck Dispatching Problem," Management Science, INFORMS, vol. 6(1), pages 80-91, October.
    2. S. F. Ghannadpour & S. Noori & R. Tavakkoli-Moghaddam, 2014. "A multi-objective vehicle routing and scheduling problem with uncertainty in customers’ request and priority," Journal of Combinatorial Optimization, Springer, vol. 28(2), pages 414-446, August.
    3. Roberto Baldacci & Aristide Mingozzi & Roberto Roberti, 2011. "New Route Relaxation and Pricing Strategies for the Vehicle Routing Problem," Operations Research, INFORMS, vol. 59(5), pages 1269-1283, October.
    4. Tao Zhang & W. Art Chaovalitwongse & Yuejie Zhang, 2014. "Integrated Ant Colony and Tabu Search approach for time dependent vehicle routing problems with simultaneous pickup and delivery," Journal of Combinatorial Optimization, Springer, vol. 28(1), pages 288-309, July.
    5. Philippe Lacomme & Christian Prins & Wahiba Ramdane-Cherif, 2004. "Competitive Memetic Algorithms for Arc Routing Problems," Annals of Operations Research, Springer, vol. 131(1), pages 159-185, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jianming Zhu & Shuyue Liu & Smita Ghosh, 2019. "Model and algorithm of routes planning for emergency relief distribution in disaster management with disaster information update," Journal of Combinatorial Optimization, Springer, vol. 38(1), pages 208-223, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liang Song & Hao Gu & Hejiao Huang, 2017. "A lower bound for the adaptive two-echelon capacitated vehicle routing problem," Journal of Combinatorial Optimization, Springer, vol. 33(4), pages 1145-1167, May.
    2. John E. Fontecha & Oscar O. Guaje & Daniel Duque & Raha Akhavan-Tabatabaei & Juan P. Rodríguez & Andrés L. Medaglia, 2020. "Combined maintenance and routing optimization for large-scale sewage cleaning," Annals of Operations Research, Springer, vol. 286(1), pages 441-474, March.
    3. Boschetti, Marco Antonio & Maniezzo, Vittorio & Strappaveccia, Francesco, 2017. "Route relaxations on GPU for vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 258(2), pages 456-466.
    4. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    5. Wang, Minxi & Wang, Yajie & Liu, Wei & Ma, Yu & Xiang, Longtao & Yang, Yunqi & Li, Xin, 2021. "How to achieve a win–win scenario between cost and customer satisfaction for cold chain logistics?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    6. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    7. Luciano Costa & Claudio Contardo & Guy Desaulniers, 2019. "Exact Branch-Price-and-Cut Algorithms for Vehicle Routing," Transportation Science, INFORMS, vol. 53(4), pages 946-985, July.
    8. Abdelkader Sbihi & Richard Eglese, 2010. "Combinatorial optimization and Green Logistics," Annals of Operations Research, Springer, vol. 175(1), pages 159-175, March.
    9. Dayarian, Iman & Crainic, Teodor Gabriel & Gendreau, Michel & Rei, Walter, 2015. "A column generation approach for a multi-attribute vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 241(3), pages 888-906.
    10. Henriette Koch & Andreas Bortfeldt & Gerhard Wäscher, 2018. "A hybrid algorithm for the vehicle routing problem with backhauls, time windows and three-dimensional loading constraints," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 40(4), pages 1029-1075, October.
    11. Ricardo Fukasawa & Laurent Poirrier, 2017. "Numerically Safe Lower Bounds for the Capacitated Vehicle Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 544-557, August.
    12. Afsar, Hasan Murat & Afsar, Sezin & Palacios, Juan José, 2021. "Vehicle routing problem with zone-based pricing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 152(C).
    13. Katrin Heßler & Stefan Irnich, 2023. "Partial Dominance in Branch-Price-and-Cut for the Basic Multicompartment Vehicle-Routing Problem," INFORMS Journal on Computing, INFORMS, vol. 35(1), pages 50-65, January.
    14. Zhang, Junlong & Lam, William H.K. & Chen, Bi Yu, 2016. "On-time delivery probabilistic models for the vehicle routing problem with stochastic demands and time windows," European Journal of Operational Research, Elsevier, vol. 249(1), pages 144-154.
    15. Yu Zhang & Zhenzhen Zhang & Andrew Lim & Melvyn Sim, 2021. "Robust Data-Driven Vehicle Routing with Time Windows," Operations Research, INFORMS, vol. 69(2), pages 469-485, March.
    16. Uchoa, Eduardo & Pecin, Diego & Pessoa, Artur & Poggi, Marcus & Vidal, Thibaut & Subramanian, Anand, 2017. "New benchmark instances for the Capacitated Vehicle Routing Problem," European Journal of Operational Research, Elsevier, vol. 257(3), pages 845-858.
    17. Bertazzi, Luca & Golden, Bruce & Wang, Xingyin, 2015. "Min–Max vs. Min–Sum Vehicle Routing: A worst-case analysis," European Journal of Operational Research, Elsevier, vol. 240(2), pages 372-381.
    18. Rossi, Roberto & Tomasella, Maurizio & Martin-Barragan, Belen & Embley, Tim & Walsh, Christopher & Langston, Matthew, 2019. "The Dynamic Bowser Routing Problem," European Journal of Operational Research, Elsevier, vol. 275(1), pages 108-126.
    19. Rafael Martinelli & Claudio Contardo, 2015. "Exact and Heuristic Algorithms for Capacitated Vehicle Routing Problems with Quadratic Costs Structure," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 658-676, November.
    20. Line Blander Reinhardt & Mads Kehlet Jepsen & David Pisinger, 2016. "The Edge Set Cost of the Vehicle Routing Problem with Time Windows," Transportation Science, INFORMS, vol. 50(2), pages 694-707, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:jcomop:v:32:y:2016:i:4:d:10.1007_s10878-015-9931-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.