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A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem

Author

Listed:
  • Seyed Mohammad Javad Mirzapour Al-E-Hashem

    (EM - EMLyon Business School)

  • Yacine Rekik
  • Ebrahim Mohammadi Hoseinhajlou

Abstract

Recently, ‘greenness' has become a very much needed condition in the transportation industry. In this study we develop a ‘green', transshipment-enabled model for the Inventory Routing Problem (IRP), in a many-to-one distribution network where demand for each product is realistically assumed to be uncertain. The proposed framework is a bi-objective stochastic programming model. The first objective function aims to minimize the expected value of the supply chain costs including inevitable shortage costs. The second objective function aims to minimize the total quantity of the greenhouse gas (GHG) emission produced by the vehicles and disposed products. We introduce a very practical innovative application of transshipment option to control transportation cost, reduce GHG emissions and absorb the uncertainty. In order to solve the proposed model an efficient hybrid algorithm combining L-shaped method (a sort of decomposition approach for stochastic optimization) and compromise programming (a well-known approach for multi-objective optimization) is proposed. The results show that how companies can make a reasonable tradeoff between the cost and environmental concerns and emphasize the role of transshipment option as a lever to improve both economic and environmental performance and absorb the demand fluctuations.

Suggested Citation

  • Seyed Mohammad Javad Mirzapour Al-E-Hashem & Yacine Rekik & Ebrahim Mohammadi Hoseinhajlou, 2019. "A hybrid L-shaped method to solve a bi-objective stochastic transshipment-enabled inventory routing problem," Post-Print hal-02312014, HAL.
    • Handle: RePEc:hal:journl:hal-02312014
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    Citations

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    Cited by:

    1. Chenbo Zhu & Juntian Yue & Jing Chen, 2022. "Green Product Development and Order Strategies for Retailers," Sustainability, MDPI, vol. 14(15), pages 1-18, August.
    2. Yann Mey Yee & Lilian Sy & Kryzia Lomibao & Josephine Dela Cruz German & Hui-Ming Wee, 2023. "Sustainable Economic Production Quantity Model Considering Greenhouse Gas and Wastewater Emissions," Sustainability, MDPI, vol. 15(4), pages 1-30, February.
    3. Rahmati, Reza & Neghabi, Hossein & Bashiri, Mahdi & Salari, Majid, 2023. "Stochastic regional-based profit-maximizing hub location problem: A sustainable overview," Omega, Elsevier, vol. 121(C).
    4. Neves-Moreira, Fábio & Almada-Lobo, Bernardo & Guimarães, Luís & Amorim, Pedro, 2022. "The multi-product inventory-routing problem with pickups and deliveries: Mitigating fluctuating demand via rolling horizon heuristics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    5. Mohammadi, S. & Al-e-Hashem, S.M.J. Mirzapour & Rekik, Y., 2020. "An integrated production scheduling and delivery route planning with multi-purpose machines: A case study from a furniture manufacturing company," International Journal of Production Economics, Elsevier, vol. 219(C), pages 347-359.
    6. S. Mohammadi & S. Al-E-Hashem & Yacine Rekik, 2020. "An integrated production scheduling and delivery route planning with multi-purpose machines: A case study from a furniture manufacturing company," Post-Print hal-02194222, HAL.
    7. Hang Thi Thanh Vu & Jeonghan Ko, 2023. "Inventory Transshipment Considering Greenhouse Gas Emissions for Sustainable Cross-Filling in Cold Supply Chains," Sustainability, MDPI, vol. 15(9), pages 1-22, April.

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