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Multi-product inventory model for cold items with cost and emission consideration

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  • Bozorgi, Ali

Abstract

While sharing storage and transportation units is common for many product types, cold items usually have different temperature requirements and as a result, not all items can share a holding/transportation unit. Consequently, the type of products and their compatibility with other products needs to be considered in the inventory model. In this paper, we propose multi-product inventory models for cold items. The models determine the inventory levels that minimize either the cost or carbon-equivalent emissions. We model the compatibility of items as a constraint in the inventory model. To solve the model, we first find an appropriate “family of products” that can share a storage/transportation unit. Then, for each family of products we develop an approximate solution method to determine the order quantity of each product within a family. Numerical experiments demonstrate the solution procedure, and provide managerial insights into cold item inventory policies.

Suggested Citation

  • Bozorgi, Ali, 2016. "Multi-product inventory model for cold items with cost and emission consideration," International Journal of Production Economics, Elsevier, vol. 176(C), pages 123-142.
    • Handle: RePEc:eee:proeco:v:176:y:2016:i:c:p:123-142
    DOI: 10.1016/j.ijpe.2016.03.011
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    3. Adarsh Kumar Singh & Nachiappan Subramanian & Kulwant Singh Pawar & Ruibin Bai, 2018. "Cold chain configuration design: location-allocation decision-making using coordination, value deterioration, and big data approximation," Annals of Operations Research, Springer, vol. 270(1), pages 433-457, November.
    4. Eleonora Bottani & Giorgia Casella & Majcol Nobili & Letizia Tebaldi, 2022. "An Analytic Model for Estimating the Economic and Environmental Impact of Food Cold Supply Chain," Sustainability, MDPI, vol. 14(8), pages 1-16, April.
    5. Zhang, Siying & Chen, Ning & Song, Xiaoming & Yang, Jia, 2019. "Optimizing decision-making of regional cold chain logistics system in view of low-carbon economy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 844-857.
    6. Basim S. O. Alsaedi & Marwan H. Ahelali, 2024. "A Sustainable Supply Chain Model with Low Carbon Emissions for Deteriorating Imperfect-Quality Items under Learning Fuzzy Theory," Mathematics, MDPI, vol. 12(8), pages 1-38, April.
    7. Yang, Yuxiang & Goodarzi, Shadi & Bozorgi, Ali & Fahimnia, Behnam, 2021. "Carbon cap-and-trade schemes in closed-loop supply chains: Why firms do not comply?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 156(C).
    8. Beatrice Marchi & Simone Zanoni & Mohamad Y. Jaber, 2020. "Energy Implications of Lot Sizing Decisions in Refrigerated Warehouses," Energies, MDPI, vol. 13(7), pages 1-13, April.
    9. Gaganis, Chrysovalantis & Galariotis, Emilios & Pasiouras, Fotios & Tasiou, Menelaos, 2023. "Managerial ability and corporate greenhouse gas emissions," Journal of Economic Behavior & Organization, Elsevier, vol. 212(C), pages 438-453.
    10. Chen, Zhixiang & Bidanda, Bopaya, 2019. "Sustainable manufacturing production-inventory decision of multiple factories with JIT logistics, component recovery and emission control," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 128(C), pages 356-383.

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