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A Two-Stage Model with an Improved Clustering Algorithm for a Distribution Center Location Problem under Uncertainty

Author

Listed:
  • Jun Wu

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

  • Xin Liu

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

  • Yuanyuan Li

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

  • Liping Yang

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

  • Wenyan Yuan

    (School of Mathematics and Physics, Beijing University of Chemical Technology, Beijing 100029, China)

  • Yile Ba

    (School of Economics and Management, Beijing University of Chemical Technology, Beijing 100029, China)

Abstract

Distribution centers are quite important for logistics. In order to save costs, reduce energy consumption and deal with increasingly uncertain demand, it is necessary for distribution centers to select the location strategically. In this paper, a two-stage model based on an improved clustering algorithm and the center-of-gravity method is proposed to deal with the multi-facility location problem arising from a real-world case. First, a distance function used in clustering is redefined to include both the spatial indicator and the socio-economic indicator. Then, an improved clustering algorithm is used to determine the optimal number of distribution centers needed and the coverage of each center. Third, the center-of-gravity method is used to determine the final location of each center. Finally, the improved method is compared with the traditional clustering method by testing data from 12 cities in Inner Mongolia Autonomous Region in China. The comparison result proves the proposed method’s effectiveness.

Suggested Citation

  • Jun Wu & Xin Liu & Yuanyuan Li & Liping Yang & Wenyan Yuan & Yile Ba, 2022. "A Two-Stage Model with an Improved Clustering Algorithm for a Distribution Center Location Problem under Uncertainty," Mathematics, MDPI, vol. 10(14), pages 1-17, July.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:14:p:2519-:d:867016
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    References listed on IDEAS

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    1. Tingting Cui & Yanfeng Ouyang & Zuo-Jun Max Shen, 2010. "Reliable Facility Location Design Under the Risk of Disruptions," Operations Research, INFORMS, vol. 58(4-part-1), pages 998-1011, August.
    2. Harwin de Vries & Joris van de Klundert & Albert P.M. Wagelmans, 2020. "The Roadside Healthcare Facility Location Problem A Managerial Network Design Challenge," Production and Operations Management, Production and Operations Management Society, vol. 29(5), pages 1165-1187, May.
    3. M. Hakan Akyüz & Temel Öncan & İ. Kuban Altınel, 2019. "Branch and bound algorithms for solving the multi-commodity capacitated multi-facility Weber problem," Annals of Operations Research, Springer, vol. 279(1), pages 1-42, August.
    4. Mohammad Rostami & Morteza Bagherpour, 2020. "A lagrangian relaxation algorithm for facility location of resource-constrained decentralized multi-project scheduling problems," Operational Research, Springer, vol. 20(2), pages 857-897, June.
    5. Lawrence V. Snyder & Mark S. Daskin, 2005. "Reliability Models for Facility Location: The Expected Failure Cost Case," Transportation Science, INFORMS, vol. 39(3), pages 400-416, August.
    6. Juan Li & Dan-dan Xiao & Hong Lei & Ting Zhang & Tian Tian, 2020. "Using Cuckoo Search Algorithm with Q -Learning and Genetic Operation to Solve the Problem of Logistics Distribution Center Location," Mathematics, MDPI, vol. 8(2), pages 1-32, January.
    7. Huizhen Zhang & Cesar Beltran-Royo & Bo Wang & Ziying Zhang, 2019. "Two-phase semi-Lagrangian relaxation for solving the uncapacitated distribution centers location problem for B2C E-commerce," Computational Optimization and Applications, Springer, vol. 72(3), pages 827-848, April.
    8. Silva, Allyson & Aloise, Daniel & Coelho, Leandro C. & Rocha, Caroline, 2021. "Heuristics for the dynamic facility location problem with modular capacities," European Journal of Operational Research, Elsevier, vol. 290(2), pages 435-452.
    9. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2021. "Robust facility location under demand uncertainty and facility disruptions," Omega, Elsevier, vol. 103(C).
    10. Yang, Zhen & Chen, Haoxun & Chu, Feng & Wang, Nengmin, 2019. "An effective hybrid approach to the two-stage capacitated facility location problem," European Journal of Operational Research, Elsevier, vol. 275(2), pages 467-480.
    11. Cui, Tingting & Ouyang, Yanfeng & Shen, Zuo-Jun Max J, 2010. "Reliable Facility Location Design under the Risk of Disruptions," University of California Transportation Center, Working Papers qt5sh2c7pw, University of California Transportation Center.
    12. Mohamed Amine Gargouri & Nadia Hamani & Nassim Mrabti & Lyes Kermad, 2021. "Optimization of the Collaborative Hub Location Problem with Metaheuristics," Mathematics, MDPI, vol. 9(21), pages 1-31, October.
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    Cited by:

    1. Wen Zhang & Xiaofeng Xu & Jun Wu & Kaijian He, 2023. "Preface to the Special Issue on “Computational and Mathematical Methods in Information Science and Engineering”," Mathematics, MDPI, vol. 11(14), pages 1-4, July.

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