IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v17y2017i4d10.1007_s11067-017-9364-z.html
   My bibliography  Save this article

A Novel Model for the Time Dependent Competitive Vehicle Routing Problem: Modified Random Topology Particle Swarm Optimization

Author

Listed:
  • M. Alinaghian

    (Isfahan University of Technology)

  • M. Ghazanfari

    (Iran University of Science and Technology)

  • N. Norouzi

    (University of Tehran)

  • H. Nouralizadeh

    (Iran University of Science and Technology)

Abstract

This paper presents a novel model for a time dependent vehicle routing problem when there is a competition between distribution companies for obtaining more sales. In a real-world situation many factors cause the time dependency of travel times, for example traffic condition on peak hours plays an essential role in outcomes of the planned schedule in urban areas. This problem is named as “Time dependent competitive vehicle routing problem” (TDVRPC) which a model is presented to satisfy the “non-passing” property. The main objectives are to minimize the travel cost and maximize the sale in order to serve customers before other rival distributors. To solve the problem, a Modified Random Topology Particle Swarm Optimization algorithm (RT-PSO) is proposed and the results are compared with branch and bound algorithm in small size problems. In large scales, comparison is done with original PSO. The results show the capability of the proposed RT-PSO method for handling this problem.

Suggested Citation

  • M. Alinaghian & M. Ghazanfari & N. Norouzi & H. Nouralizadeh, 2017. "A Novel Model for the Time Dependent Competitive Vehicle Routing Problem: Modified Random Topology Particle Swarm Optimization," Networks and Spatial Economics, Springer, vol. 17(4), pages 1185-1211, December.
    • Handle: RePEc:kap:netspa:v:17:y:2017:i:4:d:10.1007_s11067-017-9364-z
    DOI: 10.1007/s11067-017-9364-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11067-017-9364-z
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-017-9364-z?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. Hunkar Toyoglu & Oya Karasan & Bahar Kara, 2012. "A New Formulation Approach for Location-Routing Problems," Networks and Spatial Economics, Springer, vol. 12(4), pages 635-659, December.
    3. Bernhard Fleischmann & Martin Gietz & Stefan Gnutzmann, 2004. "Time-Varying Travel Times in Vehicle Routing," Transportation Science, INFORMS, vol. 38(2), pages 160-173, May.
    4. L. R. Ford & D. R. Fulkerson, 1958. "Constructing Maximal Dynamic Flows from Static Flows," Operations Research, INFORMS, vol. 6(3), pages 419-433, June.
    5. Junlong Zhang & William Lam & Bi Chen, 2013. "A Stochastic Vehicle Routing Problem with Travel Time Uncertainty: Trade-Off Between Cost and Customer Service," Networks and Spatial Economics, Springer, vol. 13(4), pages 471-496, December.
    6. Chryssi Malandraki & Mark S. Daskin, 1992. "Time Dependent Vehicle Routing Problems: Formulations, Properties and Heuristic Algorithms," Transportation Science, INFORMS, vol. 26(3), pages 185-200, August.
    7. Shangyao Yan & Fei-Yen Hsiao & Yi-Chun Chen, 2015. "Inter-School Bus Scheduling Under Stochastic Travel Times," Networks and Spatial Economics, Springer, vol. 15(4), pages 1049-1074, December.
    8. Éric Taillard & Philippe Badeau & Michel Gendreau & François Guertin & Jean-Yves Potvin, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 31(2), pages 170-186, May.
    9. Ichoua, Soumia & Gendreau, Michel & Potvin, Jean-Yves, 2003. "Vehicle dispatching with time-dependent travel times," European Journal of Operational Research, Elsevier, vol. 144(2), pages 379-396, January.
    10. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    11. G. Clarke & J. W. Wright, 1964. "Scheduling of Vehicles from a Central Depot to a Number of Delivery Points," Operations Research, INFORMS, vol. 12(4), pages 568-581, August.
    12. Qureshi, A.G. & Taniguchi, E. & Yamada, T., 2009. "An exact solution approach for vehicle routing and scheduling problems with soft time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(6), pages 960-977, November.
    13. Fred Glover & Eugene Woolsey, 1974. "Technical Note—Converting the 0-1 Polynomial Programming Problem to a 0-1 Linear Program," Operations Research, INFORMS, vol. 22(1), pages 180-182, February.
    14. A. W. J. Kolen & A. H. G. Rinnooy Kan & H. W. J. M. Trienekens, 1987. "Vehicle Routing with Time Windows," Operations Research, INFORMS, vol. 35(2), pages 266-273, April.
    15. Beasley, JE, 1981. "Adapting the savings algorithm for varying inter-customer travel times," Omega, Elsevier, vol. 9(6), pages 658-659.
    16. Seyedmehdi Mirmohammadsadeghi & Shamsuddin Ahmed, 2015. "Memetic Heuristic Approach for Solving Truck and Trailer Routing Problems with Stochastic Demands and Time Windows," Networks and Spatial Economics, Springer, vol. 15(4), pages 1093-1115, December.
    17. Christophe Duhamel & Jean-Yves Potvin & Jean-Marc Rousseau, 1997. "A Tabu Search Heuristic for the Vehicle Routing Problem with Backhauls and Time Windows," Transportation Science, INFORMS, vol. 31(1), pages 49-59, February.
    18. The Jin Ai & Voratas Kachitvichyanukul, 2009. "A Particle Swarm Optimisation for Vehicle Routing Problem with Time Windows," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 6(4), pages 519-537.
    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. Qingqing Qiao & Fengming Tao & Hailin Wu & Xuewei Yu & Mengjun Zhang, 2020. "Optimization of a Capacitated Vehicle Routing Problem for Sustainable Municipal Solid Waste Collection Management Using the PSO-TS Algorithm," IJERPH, MDPI, vol. 17(6), pages 1-22, March.
    2. Samuel Reong & Hui-Ming Wee & Yu-Lin Hsiao, 2022. "20 Years of Particle Swarm Optimization Strategies for the Vehicle Routing Problem: A Bibliometric Analysis," Mathematics, MDPI, vol. 10(19), pages 1-19, October.
    3. Mohammad Tamannaei & Hamid Zarei & Sajede Aminzadegan, 2021. "A Game-Theoretic Approach to the Freight Transportation Pricing Problem in the Presence of Intermodal Service Providers in a Competitive Market," Networks and Spatial Economics, Springer, vol. 21(1), pages 123-173, March.

    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. 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.
    2. W Maden & R Eglese & D Black, 2010. "Vehicle routing and scheduling with time-varying data: A case study," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 515-522, March.
    3. 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.
    4. Müller, Juliane, 2010. "Approximative solutions to the bicriterion Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 202(1), pages 223-231, April.
    5. Andres Figliozzi, Miguel, 2012. "The time dependent vehicle routing problem with time windows: Benchmark problems, an efficient solution algorithm, and solution characteristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(3), pages 616-636.
    6. Xiao, Yiyong & Konak, Abdullah, 2016. "The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 88(C), pages 146-166.
    7. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    8. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    9. Lagos, Felipe & Pereira, Jordi, 2024. "Multi-armed bandit-based hyper-heuristics for combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 312(1), pages 70-91.
    10. Rincon-Garcia, Nicolas & Waterson, Ben & Cherrett, Tom J. & Salazar-Arrieta, Fernando, 2020. "A metaheuristic for the time-dependent vehicle routing problem considering driving hours regulations – An application in city logistics," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 429-446.
    11. Ampol Karoonsoontawong & Puntipa Punyim & Wanvara Nueangnitnaraporn & Vatanavongs Ratanavaraha, 2020. "Multi-Trip Time-Dependent Vehicle Routing Problem with Soft Time Windows and Overtime Constraints," Networks and Spatial Economics, Springer, vol. 20(2), pages 549-598, June.
    12. Sébastien Mouthuy & Florence Massen & Yves Deville & Pascal Van Hentenryck, 2015. "A Multistage Very Large-Scale Neighborhood Search for the Vehicle Routing Problem with Soft Time Windows," Transportation Science, INFORMS, vol. 49(2), pages 223-238, May.
    13. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    14. Sana Jawarneh & Salwani Abdullah, 2015. "Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-23, July.
    15. Loske, Dominic & Klumpp, Matthias, 2021. "Human-AI collaboration in route planning: An empirical efficiency-based analysis in retail logistics," International Journal of Production Economics, Elsevier, vol. 241(C).
    16. Tomáš Režnar & Jan Martinovič & Kateřina Slaninová & Ekaterina Grakova & Vít Vondrák, 2017. "Probabilistic time-dependent vehicle routing problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 545-560, September.
    17. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    18. Kritikos, Manolis N. & Ioannou, George, 2010. "The balanced cargo vehicle routing problem with time windows," International Journal of Production Economics, Elsevier, vol. 123(1), pages 42-51, January.
    19. Maria João Santos & Pedro Amorim & Alexandra Marques & Ana Carvalho & Ana Póvoa, 2020. "The vehicle routing problem with backhauls towards a sustainability perspective: a review," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(2), pages 358-401, July.
    20. Anke Stieber & Armin Fügenschuh, 2022. "Dealing with time in the multiple traveling salespersons problem with moving targets," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 991-1017, September.

    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:kap:netspa:v:17:y:2017:i:4:d:10.1007_s11067-017-9364-z. 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.