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A hierarchical process industry production-distribution planning model

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  • Das, K.
  • Sengupta, S.

Abstract

Global and multinational companies are subject to government regulations in addition to other international uncertainties due to operation in diverse geographic locations. Such government regulations often affect the cost of raw materials adversely which in turn creates adverse impact on product cost and forces the decision makers to re-evaluate current production-distribution plan. This paper presents an integrated supply chain model for simultaneous strategic and operational planning of a strategic business unit (SBU) in a global supply chain affected by government regulations. The model incorporates impact of changes in cost of inputs on expected product cost and solves for an optimal strategic and operational plan for the entire supply chain. In addition, the model includes exchange rates, border crossing costs and solves a multi-period model with due consideration of uncertainties in demand and transportation time.

Suggested Citation

  • Das, K. & Sengupta, S., 2009. "A hierarchical process industry production-distribution planning model," International Journal of Production Economics, Elsevier, vol. 117(2), pages 402-419, February.
    • Handle: RePEc:eee:proeco:v:117:y:2009:i:2:p:402-419
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    Cited by:

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    2. Gylling, Michael & Heikkilä, Jussi & Jussila, Kari & Saarinen, Markku, 2015. "Making decisions on offshore outsourcing and backshoring: A case study in the bicycle industry," International Journal of Production Economics, Elsevier, vol. 162(C), pages 92-100.
    3. Jabbarzadeh, Armin & Haughton, Michael & Pourmehdi, Fahime, 2019. "A robust optimization model for efficient and green supply chain planning with postponement strategy," International Journal of Production Economics, Elsevier, vol. 214(C), pages 266-283.
    4. Jabbarzadeh, Armin & Fahimnia, Behnam & Sheu, Jiuh-Biing, 2017. "An enhanced robustness approach for managing supply and demand uncertainties," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 620-631.
    5. Feng, Cheng-Min & Wu, Pei-Ju, 2009. "A tax savings model for the emerging global manufacturing network," International Journal of Production Economics, Elsevier, vol. 122(2), pages 534-546, December.
    6. Liu, Songsong & Papageorgiou, Lazaros G., 2013. "Multiobjective optimisation of production, distribution and capacity planning of global supply chains in the process industry," Omega, Elsevier, vol. 41(2), pages 369-382.
    7. Verny, Jerome & Grigentin, Christophe, 2009. "Container shipping on the Northern Sea Route," International Journal of Production Economics, Elsevier, vol. 122(1), pages 107-117, November.
    8. 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.
    9. M Kannegiesser & H-O Günther, 2011. "An integrated optimization model for managing the global value chain of a chemical commodities manufacturer," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(4), pages 711-721, April.

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