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Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm

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  • Imen Harbaoui Dridi
  • Essia Ben Alaïa
  • Pierre Borne
  • Hanen Bouchriha

Abstract

Many sectors in the transport industry are concerned about the vehicle routing problem (VRP), hence the growing interest of researchers for this type of problem and its variants. This is due essentially to its many real applications in logistics for the transport of goods. The originality and contribution of our work is that we have dealt a problem that combines several variants: multiple vehicles (m), multiple depots (MD), pickup and delivery problem (PDP) with time windows (TW). Hence the notation of our problem: m-MDPDPTW. In this paper, we present the m-MDPDPTW, which is an optimisation problem belonging to the category of NP Hard problems. This problem must meet requests for transport between customers and suppliers satisfying precedence, capacity and time constraints. The goal is to find the best solution, which is the best route minimising the total travelled distance. To solve and optimise our m-MDPDPTW, we have developed a new algorithm based on the particle swarm optimisation (PSO) method. The performance of this new approach is tested on data set instances of Li and Lim's benchmark problems in which we have added multiple depot locations. Comparing with prior works, our proposed approach gave better results by decreasing the distance for several studied instances.

Suggested Citation

  • Imen Harbaoui Dridi & Essia Ben Alaïa & Pierre Borne & Hanen Bouchriha, 2020. "Optimisation of the multi-depots pick-up and delivery problems with time windows and multi-vehicles using PSO algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 58(14), pages 4201-4214, July.
    • Handle: RePEc:taf:tprsxx:v:58:y:2020:i:14:p:4201-4214
    DOI: 10.1080/00207543.2019.1650975
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    Cited by:

    1. Yan, Jingjing & Zhang, Huan & Wang, Yaran & Zhu, Zhaozhe & Bai, He & Li, Qicheng & Zheng, Lijun & Gao, Xinyong & You, Shijun, 2023. "Difference analysis and recognition of hydraulic oscillation by two types of sudden faults on long-distance district heating pipeline," Energy, Elsevier, vol. 284(C).
    2. Yaoting Huang & Boyu Chen & Wenlian Lu & Zhong-Xiao Jin & Ren Zheng, 2022. "Asynchronous optimization of part logistics routing problem," Journal of Global Optimization, Springer, vol. 82(4), pages 803-834, April.
    3. Du, Jianhui & Zhang, Zhiqin & Wang, Xu & Lau, Hoong Chuin, 2023. "A hierarchical optimization approach for dynamic pickup and delivery problem with LIFO constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. Huang, Baobin & Tang, Lixin & Baldacci, Roberto & Wang, Gongshu & Sun, Defeng, 2023. "A metaheuristic algorithm for a locomotive routing problem arising in the steel industry," European Journal of Operational Research, Elsevier, vol. 308(1), pages 385-399.
    5. Jarosław Ziółkowski & Aleksandra Lęgas & Elżbieta Szymczyk & Jerzy Małachowski & Mateusz Oszczypała & Joanna Szkutnik-Rogoż, 2022. "Optimization of the Delivery Time within the Distribution Network, Taking into Account Fuel Consumption and the Level of Carbon Dioxide Emissions into the Atmosphere," Energies, MDPI, vol. 15(14), pages 1-22, July.

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