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Study on Sustainable Combined Location-Inventory-Routing Problem Based on Demand Forecasting

Author

Listed:
  • Tingting Ji

    (School of Business Administration, Northeastern University, Shenyang 110167, China)

  • Shoufeng Ji

    (School of Business Administration, Northeastern University, Shenyang 110167, China)

  • Yuanyuan Ji

    (School of Business Administration, Northeastern University, Shenyang 110167, China)

  • Hongyu Liu

    (School of Business Administration, Northeastern University, Shenyang 110167, China)

Abstract

The sustainable combined location-inventory-routing problem (CLIRP) based on demand forecasting is studied in this paper. Based on the construction of a multi-stage demand forecasting model, five parts of total logistics costs: the costs of trunk transportation and regional transportation, the fixed costs of distribution center construction, the inventory holding costs, shortage costs, and salvage, are comprehensively considered. The existing CLIRP model does not consider the environmental influence. Thus, a sustainable CLIRP model considering carbon emission is established with minimum logistics costs and emission as the objective function. A heuristic algorithm gives the initial solution, and then a hybrid heuristic algorithm combining the tabu search algorithm with the simulated annealing algorithm is proposed to find the global near-optimal solution. Finally, a numerical example of a garment chain enterprise is given to illustrate the solving process of the model. The results show that using the proposed algorithm determines the optimal locations of RDCs, and the transportation routes with each region are obtained with the minimum total logistics costs and carbon emission. The model realizes the combination of location, inventory, and routing problems of the large garment enterprises and finally realizes the goal of optimizing the sustainable logistics distribution network of the garment industry, which verifies the effectiveness of the model. Moreover, a comparison is made to show the efficiency of the proposed algorithm; the results show that the proposed algorithm in this paper optimizes the route and selections of RDCs.

Suggested Citation

  • Tingting Ji & Shoufeng Ji & Yuanyuan Ji & Hongyu Liu, 2022. "Study on Sustainable Combined Location-Inventory-Routing Problem Based on Demand Forecasting," Sustainability, MDPI, vol. 14(23), pages 1-21, December.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16279-:d:995019
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    References listed on IDEAS

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    1. Darvish, Maryam & Coelho, Leandro C., 2018. "Sequential versus integrated optimization: Production, location, inventory control, and distribution," European Journal of Operational Research, Elsevier, vol. 268(1), pages 203-214.
    2. Qu, Wendy W. & Bookbinder, James H. & Iyogun, Paul, 1999. "An integrated inventory-transportation system with modified periodic policy for multiple products," European Journal of Operational Research, Elsevier, vol. 115(2), pages 254-269, June.
    3. Escalona, P. & Ordóñez, F. & Marianov, V., 2015. "Joint location-inventory problem with differentiated service levels using critical level policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 83(C), pages 141-157.
    4. 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.
    5. Zare Mehrjerdi, Yahia & Nadizadeh, Ali, 2013. "Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands," European Journal of Operational Research, Elsevier, vol. 229(1), pages 75-84.
    6. Shang, Xiaoting & Zhang, Guoqing & Jia, Bin & Almanaseer, Mohammed, 2022. "The healthcare supply location-inventory-routing problem: A robust approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    7. Zheng, Xiaojin & Yin, Meixia & Zhang, Yanxia, 2019. "Integrated optimization of location, inventory and routing in supply chain network design," Transportation Research Part B: Methodological, Elsevier, vol. 121(C), pages 1-20.
    8. Veenstra, Marjolein & Roodbergen, Kees Jan & Coelho, Leandro C. & Zhu, Stuart X., 2018. "A simultaneous facility location and vehicle routing problem arising in health care logistics in the Netherlands," European Journal of Operational Research, Elsevier, vol. 268(2), pages 703-715.
    9. Oscar Trull & Juan Carlos García-Díaz & Alicia Troncoso, 2020. "Initialization Methods for Multiple Seasonal Holt–Winters Forecasting Models," Mathematics, MDPI, vol. 8(2), pages 1-16, February.
    10. Schenekemberg, Cleder M. & Scarpin, Cassius T. & Pécora, José E. & Guimarães, Thiago A. & Coelho, Leandro C., 2021. "The two-echelon production-routing problem," European Journal of Operational Research, Elsevier, vol. 288(2), pages 436-449.
    11. Felix T.S. Chan & Z.X. Wang & A. Goswami & A. Singhania & M.K. Tiwari, 2020. "Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations," International Journal of Production Research, Taylor & Francis Journals, vol. 58(17), pages 5155-5174, September.
    12. Luca Bertazzi & Maria Grazia Speranza, 2002. "Continuous and Discrete Shipping Strategies for the Single Link Problem," Transportation Science, INFORMS, vol. 36(3), pages 314-325, August.
    13. Tuzun, Dilek & Burke, Laura I., 1999. "A two-phase tabu search approach to the location routing problem," European Journal of Operational Research, Elsevier, vol. 116(1), pages 87-99, July.
    14. Han, Dongya & Yang, Yongjian & Wang, Dujuan & Cheng, T.C.E. & Yin, Yunqiang, 2019. "Integrated production, inventory, and outbound distribution operations with fixed departure times in a three-stage supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 334-347.
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