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Designing optimal global supply chains at Dow AgroSciences

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  • Matt Bassett
  • Leslie Gardner

Abstract

The design of the underlying supply chain network can have a tremendous impact on the profitability, manageability, and level of risk of a global supply chain. Taxes, duties, and tariffs vary from country to country as well as trading bloc to trading bloc and can consume as much as 10% of the revenues of certain products. In the highly regulated business environment of agricultural chemicals, the country of origin of an active ingredient can determine where the final product can be marketed and the amount of taxes and duties applied to the product, making it necessary to trace all batches of product through many layers of the supply chain to their sources. This article presents a mixed integer linear programming model in use at Dow AgroSciences LLC that simultaneously optimizes the network design underlying global supply chains and the monthly production and shipping schedules for maximum profitability. This work contributes to the supply chain design literature by demonstrating a novel method of tracing products to their source for inventory valuation, taxation, and duty computation in a production environment where the products change into other products as they pass through nodes in the network. It also demonstrates an iterative scheme for determining unit fixed costs for fixed cost allocation for the same purposes. Finally, it provides a case study of a supply chain design initiative in a global enterprise. Copyright Springer Science+Business Media, LLC 2013

Suggested Citation

  • Matt Bassett & Leslie Gardner, 2013. "Designing optimal global supply chains at Dow AgroSciences," Annals of Operations Research, Springer, vol. 203(1), pages 187-216, March.
    • Handle: RePEc:spr:annopr:v:203:y:2013:i:1:p:187-216:10.1007/s10479-010-0802-2
    DOI: 10.1007/s10479-010-0802-2
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    1. Jahani, Hamed & Abbasi, Babak & Sheu, Jiuh-Biing & Klibi, Walid, 2024. "Supply chain network design with financial considerations: A comprehensive review," European Journal of Operational Research, Elsevier, vol. 312(3), pages 799-839.
    2. Jahani, Hamed & Abbasi, Babak & Alavifard, Farzad & Talluri, Srinivas, 2018. "Supply chain network redesign with demand and price uncertainty," International Journal of Production Economics, Elsevier, vol. 205(C), pages 287-312.
    3. Christos Lemonakis & Nikolaos Sariannidis & Alexandros Garefalakis & Anastasia Adamou, 2020. "Visualizing operational effects of ERP systems through graphical representations: current trends and perspectives," Annals of Operations Research, Springer, vol. 294(1), pages 401-418, November.
    4. Peyman Taki & Farnaz Barzinpour & Ebrahim Teimoury, 2016. "Risk-pooling strategy, lead time, delivery reliability and inventory control decisions in a stochastic multi-objective supply chain network design," Annals of Operations Research, Springer, vol. 244(2), pages 619-646, September.

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