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A bi-objective location-inventory model with capacitated transportation and lateral transshipments

Author

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  • Ghazaleh Ahmadi
  • S. Ali Torabi
  • Reza Tavakkoli-Moghaddam

Abstract

We integrate location and inventory decisions in a three-echelon distribution network model with multiple products, capacitated in-house fleet and proactive transshipments between depots. The problem was originally motivated by the real-life case of a leading company in consumers’ household goods. The company offers a wide range of products which are different from demand pattern and shortage viewpoints. One of the product groups has seasonal trend with possibly lost sales during high seasons and backlog in low seasons, while the others lack any seasonal trend and get backlogged if any shortage occurs. A two-step process consisting of a new practical customer classification framework and a new mathematical model is developed. Total profit and customers’ dissatisfaction in the form of a new service-level measure are considered as the objective functions. To study the effects of transportation capacity on the network’s performance, a second scenario with inclusion of third-party transportation resources is presented. Due to unavailability or insufficiency of required objective data about production capacities and demands, they are assumed to be imprecise (i.e. possibilistic). After converting the original fuzzy model to its equivalent crisp formulation, an interactive solution procedure is applied to deal with the trade-off between the conflicting objectives. Useful managerial insights are also derived from the numerical experiments.

Suggested Citation

  • Ghazaleh Ahmadi & S. Ali Torabi & Reza Tavakkoli-Moghaddam, 2016. "A bi-objective location-inventory model with capacitated transportation and lateral transshipments," International Journal of Production Research, Taylor & Francis Journals, vol. 54(7), pages 2035-2056, April.
    • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:7:p:2035-2056
    DOI: 10.1080/00207543.2015.1082042
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    Cited by:

    1. Pourya Pourhejazy & Oh Kyoung Kwon, 2016. "The New Generation of Operations Research Methods in Supply Chain Optimization: A Review," Sustainability, MDPI, vol. 8(10), pages 1-23, October.
    2. Naderi, Siamak & Kilic, Kemal & Dasci, Abdullah, 2020. "A deterministic model for the transshipment problem of a fast fashion retailer under capacity constraints," International Journal of Production Economics, Elsevier, vol. 227(C).
    3. Feng, Xuehao & Moon, Ilkyeong & Ryu, Kwangyeol, 2017. "Warehouse capacity sharing via transshipment for an integrated two-echelon supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 104(C), pages 17-35.
    4. Nasiri, G. Reza & Deymeh, Hadi & Karimi, Behrooz & Miandoabchi, Elnaz, 2021. "Incorporating sales and marketing considerations into a competitive multi-echelon distribution network design problem with pricing strategy in a stochastic environment," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    5. Ting Qu & Tianxiang Huang & Duxian Nie & Yelin Fu & Lin Ma & George Q. Huang, 2022. "Joint Decisions of Inventory Optimization and Order Allocation for Omni-Channel Multi-Echelon Distribution Network," Sustainability, MDPI, vol. 14(10), pages 1-23, May.
    6. Behnam Vahdani & Elham Ahmadzadeh, 2021. "Incorporating Price-Dependent Demands into a Multi-Echelon Closed-Loop Network Considering the Lost Sales and Backorders: a Case Study of Wireless Network," Networks and Spatial Economics, Springer, vol. 21(3), pages 639-680, September.

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