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Location Selection for Regional Logistics Center Based on Particle Swarm Optimization

Author

Listed:
  • Yingyi Huang

    (School of Business, Ningbo Tech University, Ningbo 315104, China
    School of Business, Quanzhou Normal University, Quanzhou 362046, China)

  • Xinyu Wang

    (School of Business, Quanzhou Normal University, Quanzhou 362046, China
    School of Logistics Management & Engineering, Nanning Normal University, Nanning 530011, China)

  • Hongyan Chen

    (School of Economics & Management, Quanzhou University of Information Engineering, Quanzhou 362046, China)

Abstract

The location of a logistics center is very important in a logistics system, as the success of the location determines the whole logistics system’s structure, shape, and mode, and not only affects the logistics center’s own operating costs, performance, and future development, but also affects the operation of the entire logistics system. Therefore, the selection of the location for a logistics center has great significance for improving the efficiency of regional logistics and optimizing the structure of a logistics system. This study constructed a multi-factor constrained P-median site-selection model to optimize the locations of logistics centers to improve the efficiency of logistics and optimize the structure of the logistics system in a region. The results show that the optimal distribution of logistics center sites and the coverage of freight capacity demand derived from the particle swarm algorithm are more balanced than those derived by the other algorithm. Following the comparison of the results for the utility of the optimized layout points solved by the particle swarm algorithm and the immune genetic algorithm, it is concluded that the optimal fitness value obtained by the particle swarm algorithm is lower than the other. It is proven that the particle swarm algorithm of the P-median site-selection model under this multi-factor constraint has some reference value for the selection of the sites of multi-logistics centers.

Suggested Citation

  • Yingyi Huang & Xinyu Wang & Hongyan Chen, 2022. "Location Selection for Regional Logistics Center Based on Particle Swarm Optimization," Sustainability, MDPI, vol. 14(24), pages 1-10, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:24:p:16409-:d:997005
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    References listed on IDEAS

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    1. Murray, Alan T. & Church, Richard L. & Feng, Xin, 2020. "Single facility siting involving allocation decisions," European Journal of Operational Research, Elsevier, vol. 284(3), pages 834-846.
    2. Kyosang Hwang & Tooba Binte Asif & Taesik Lee, 2022. "Choice-driven location-allocation model for healthcare facility location problem," Flexible Services and Manufacturing Journal, Springer, vol. 34(4), pages 1040-1065, December.
    3. Carrasco Heine, Oscar F. & Demleitner, Antonia & Matuschke, Jannik, 2023. "Bifactor approximation for location routing with vehicle and facility capacities," European Journal of Operational Research, Elsevier, vol. 304(2), pages 429-442.
    4. Aziz, Haris & Chan, Hau & Lee, Barton E. & Parkes, David C., 2020. "The capacity constrained facility location problem," Games and Economic Behavior, Elsevier, vol. 124(C), pages 478-490.
    5. Sophie N. Parragh & Fabien Tricoire & Walter J. Gutjahr, 2022. "A branch-and-Benders-cut algorithm for a bi-objective stochastic facility location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(2), pages 419-459, June.
    6. Weiqiao Wang & Kai Yang & Lixing Yang & Ziyou Gao, 2022. "Tractable approximations for the distributionally robust conditional vertex p-center problem: Application to the location of high-speed railway emergency rescue stations," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 73(3), pages 525-539, March.
    7. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2021. "Robust facility location under demand uncertainty and facility disruptions," Omega, Elsevier, vol. 103(C).
    8. Ateekh Ur Rehman & Mustufa Haider Abidi & Usama Umer & Yusuf Siraj Usmani, 2019. "Multi-Criteria Decision-Making Approach for Selecting Wind Energy Power Plant Locations," Sustainability, MDPI, vol. 11(21), pages 1-20, November.
    9. Corberán, Ángel & Landete, Mercedes & Peiró, Juanjo & Saldanha-da-Gama, Francisco, 2020. "The facility location problem with capacity transfers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    10. Rui Chi & Yixin Su & Zhijian Qu & Xuexin Chi, 2019. "A Hybridization of Cuckoo Search and Differential Evolution for the Logistics Distribution Center Location Problem," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-16, February.
    11. Hongzhi Wang & Haojie Ran & Xiaohong Dang, 2022. "Location Optimization of Fresh Agricultural Products Cold Chain Distribution Center under Carbon Emission Constraints," Sustainability, MDPI, vol. 14(11), pages 1-24, May.
    12. Wu, Tao & Huang, Le & Liang, Zhe & Zhang, Xiaoning & Zhang, Canrong, 2022. "A supervised learning-driven heuristic for solving the facility location and production planning problem," European Journal of Operational Research, Elsevier, vol. 301(2), pages 785-796.
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