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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
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    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.
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    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.

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