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A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion

Author

Listed:
  • Maryam Dehghan Chenary

    (Department of Business Decisions and Analytics, University of Vienna, 1090 Wien, Austria)

  • Arman Ferdowsi

    (ECS Group, TU Wien, 1040 Wien, Austria)

  • Richard F. Hartl

    (Department of Business Decisions and Analytics, University of Vienna, 1090 Wien, Austria)

Abstract

Background : This paper introduces an enhanced multi-period p -mobile hub location model that accounts for critical factors such as service time, flow processing delays, and congestion impacts at capacity-constrained hubs. As (urban) transportation networks evolve, mobile hubs play an increasingly vital role in promoting sustainable logistics solutions and addressing complex operational challenges. By enabling the repositioning of hubs across periods, this model seeks to minimize overall costs, particularly in response to dynamic demand fluctuations. Method : To solve this problem, we propose a bi-objective optimization model and introduce a hybrid meta-heuristic algorithm tailored to this application. The algorithm involves a clustering-based technique for evaluating solutions and a refined genetic approach for producing new sets of solutions. Results : Various experiments have been conducted on the Australian Post dataset to evaluate the proposed method. The results have been compared with Multiple-Objecti-ve Particle Swarm Optimization (MOPSO) and Non-Domi-nated Sorting Genetic Algorithm (NSGA-II) using several performance evaluation metrics. Conclusions : The results indicate that the proposed algorithm can provide remarkably better Pareto sets than the other competitive algorithms.

Suggested Citation

  • Maryam Dehghan Chenary & Arman Ferdowsi & Richard F. Hartl, 2024. "A Pareto-Based Clustering Approach for Solving a Bi-Objective Mobile Hub Location Problem with Congestion," Logistics, MDPI, vol. 8(4), pages 1-30, December.
    • Handle: RePEc:gam:jlogis:v:8:y:2024:i:4:p:130-:d:1540778
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    References listed on IDEAS

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    1. Rodríguez, V. & Alvarez, M.J. & Barcos, L., 2007. "Hub location under capacity constraints," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 495-505, September.
    2. Sibel A. Alumur & Stefan Nickel & Francisco Saldanha-da-Gama & Yusuf Seçerdin, 2016. "Multi-period hub network design problems with modular capacities," Annals of Operations Research, Springer, vol. 246(1), pages 289-312, November.
    3. Campbell, James F., 1994. "Integer programming formulations of discrete hub location problems," European Journal of Operational Research, Elsevier, vol. 72(2), pages 387-405, January.
    4. Lipowski, Adam & Lipowska, Dorota, 2012. "Roulette-wheel selection via stochastic acceptance," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(6), pages 2193-2196.
    5. James F. Campbell & Morton E. O'Kelly, 2012. "Twenty-Five Years of Hub Location Research," Transportation Science, INFORMS, vol. 46(2), pages 153-169, May.
    6. Correia, Isabel & Nickel, Stefan & Saldanha-da-Gama, Francisco, 2010. "Single-assignment hub location problems with multiple capacity levels," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1047-1066, September.
    7. Alumur, Sibel & Kara, Bahar Y., 2008. "Network hub location problems: The state of the art," European Journal of Operational Research, Elsevier, vol. 190(1), pages 1-21, October.
    8. Derya Celik Turkoglu & Mujde Erol Genevois, 2020. "A comparative survey of service facility location problems," Annals of Operations Research, Springer, vol. 292(1), pages 399-468, September.
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