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Hub-and-spoke network design under congestion: A learning based metaheuristic

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  • Karimi-Mamaghan, Maryam
  • Mohammadi, Mehrdad
  • Pirayesh, Amir
  • Karimi-Mamaghan, Amir Mohammad
  • Irani, Hassan

Abstract

This paper models a single allocation multi-commodity hub-and-spoke network problem through a bi-objective mathematical model, considering the congestion in both hubs and connection links. A novel aggregation model is developed based on a general GI/G/c queuing system to evaluate the congestion of the flow of the multiple products in the hubs. The proposed model is then solved using a novel learning-based metaheuristic based on NSGA-II, k-Means clustering method, and an Iterated Local Search (ILS) algorithm. The proposed model and solution algorithm are validated through a set of experiments against optimal solutions, and benchmarked against four existing well-known algorithms.

Suggested Citation

  • Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Pirayesh, Amir & Karimi-Mamaghan, Amir Mohammad & Irani, Hassan, 2020. "Hub-and-spoke network design under congestion: A learning based metaheuristic," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:transe:v:142:y:2020:i:c:s1366554520307201
    DOI: 10.1016/j.tre.2020.102069
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    References listed on IDEAS

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    Cited by:

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    2. Yang, Lingxiao & Zheng, Jianfeng & Wang, Jian & Hu, Xiaowei, 2023. "The maximal detour liner shipping hub location problem: Improving the applicability of the p-hub center problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Mohammadi, Mehrdad & Dehghan, Milad & Pirayesh, Amir & Dolgui, Alexandre, 2022. "Bi‐objective optimization of a stochastic resilient vaccine distribution network in the context of the COVID‐19 pandemic," Omega, Elsevier, vol. 113(C).
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    5. Karimi-Mamaghan, Maryam & Mohammadi, Mehrdad & Pasdeloup, Bastien & Meyer, Patrick, 2023. "Learning to select operators in meta-heuristics: An integration of Q-learning into the iterated greedy algorithm for the permutation flowshop scheduling problem," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1296-1330.
    6. Mohri, Seyed Sina & Mohammadi, Mehrdad & Gendreau, Michel & Pirayesh, Amir & Ghasemaghaei, Ali & Salehi, Vahid, 2022. "Hazardous material transportation problems: A comprehensive overview of models and solution approaches," European Journal of Operational Research, Elsevier, vol. 302(1), pages 1-38.
    7. Domínguez-Bravo, Carmen-Ana & Fernández, Elena & Lüer-Villagra, Armin, 2024. "Hub location with congestion and time-sensitive demand," European Journal of Operational Research, Elsevier, vol. 316(3), pages 828-844.
    8. Jahani, Hamed & Chaleshtori, Amir Eshaghi & Khaksar, Seyed Mohammad Sadegh & Aghaie, Abdollah & Sheu, Jiuh-Biing, 2022. "COVID-19 vaccine distribution planning using a congested queuing system—A real case from Australia," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).

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