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Strategic optimization of wheat supply chain network under uncertainty: a real case study

Author

Listed:
  • Seyyed-Mahdi Hosseini-Motlagh

    (Iran University of Science and Technology)

  • Mohammad Reza Ghatreh Samani

    (Iran University of Science and Technology)

  • Firoozeh Abbasi Saadi

    (Iran University of Science and Technology)

Abstract

Today, wheat and its by-products are considered the most important food grain source for humans across the world. Accordingly, integrally investigating the wheat supply chain is of great importance in strategic decisions. In this respect, this paper addresses a real case study of wheat supply chain in Iran as well as the entities involved it. Presenting a new mathematical model, the total cost of the wheat supply chain network design is optimized. The proposed model integrates collection, production, inventory, and distribution echelons of the wheat supply chain, simultaneously. The inherent uncertainty in supply, demand, related costs, and climate changing result in the different quality of wheat which make it challenging to design and manage an optimal structure for the wheat supply chain network. Hence, the role of uncertainty in the mathematical optimization model is highlighted, and then, a robust approach is utilized to tackle the inevitable uncertainty of parameters. The proposed robust model not only manage to overcome the complexity of uncertainty but also outperform the deterministic model. It shows the proposed robust model is more effective than deterministic one that can be applied to make robust strategic and tactical decisions for the wheat supply chain. Moreover, the sensitivity analysis of influential parameters is conducted. Finally, according to the obtained results as well as sensitivity analysis, some managerial insights are provided.

Suggested Citation

  • Seyyed-Mahdi Hosseini-Motlagh & Mohammad Reza Ghatreh Samani & Firoozeh Abbasi Saadi, 2021. "Strategic optimization of wheat supply chain network under uncertainty: a real case study," Operational Research, Springer, vol. 21(3), pages 1487-1527, September.
  • Handle: RePEc:spr:operea:v:21:y:2021:i:3:d:10.1007_s12351-019-00515-y
    DOI: 10.1007/s12351-019-00515-y
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    1. Amorim, Pedro & Curcio, Eduardo & Almada-Lobo, Bernardo & Barbosa-Póvoa, Ana P.F.D. & Grossmann, Ignacio E., 2016. "Supplier selection in the processed food industry under uncertainty," European Journal of Operational Research, Elsevier, vol. 252(3), pages 801-814.
    2. M T Lucas & D Chhajed, 2004. "Applications of location analysis in agriculture: a survey," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(6), pages 561-578, June.
    3. V. R. Ghezavati & S. Hooshyar & R. Tavakkoli-Moghaddam, 2017. "A Benders’ decomposition algorithm for optimizing distribution of perishable products considering postharvest biological behavior in agri-food supply chain: a case study of tomato," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(1), pages 29-54, March.
    4. Andrés Weintraub & Carlos Romero, 2006. "Operations Research Models and the Management of Agricultural and Forestry Resources: A Review and Comparison," Interfaces, INFORMS, vol. 36(5), pages 446-457, October.
    5. Shiva Zokaee & Armin Jabbarzadeh & Behnam Fahimnia & Seyed Jafar Sadjadi, 2017. "Robust supply chain network design: an optimization model with real world application," Annals of Operations Research, Springer, vol. 257(1), pages 15-44, October.
    6. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    7. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    8. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    9. Ge, Houtian & Nolan, James & Gray, Richard & Goetz, Stephan & Han, Yicheol, 2016. "Supply chain complexity and risk mitigation – A hybrid optimization–simulation model," International Journal of Production Economics, Elsevier, vol. 179(C), pages 228-238.
    10. Bilgen, Bilge & Ozkarahan, Irem, 2007. "A mixed-integer linear programming model for bulk grain blending and shipping," International Journal of Production Economics, Elsevier, vol. 107(2), pages 555-571, June.
    11. Jena, Sanjay Dominik & Poggi, Marcus, 2013. "Harvest planning in the Brazilian sugar cane industry via mixed integer programming," European Journal of Operational Research, Elsevier, vol. 230(2), pages 374-384.
    12. Farahani, Reza Zanjirani & Elahipanah, Mahsa, 2008. "A genetic algorithm to optimize the total cost and service level for just-in-time distribution in a supply chain," International Journal of Production Economics, Elsevier, vol. 111(2), pages 229-243, February.
    13. Aliakbar Hasani & Seyed Hessameddin Zegordi & Ehsan Nikbakhsh, 2015. "Robust closed-loop global supply chain network design under uncertainty: the case of the medical device industry," International Journal of Production Research, Taylor & Francis Journals, vol. 53(5), pages 1596-1624, March.
    14. Banasik, Aleksander & Kanellopoulos, Argyris & Claassen, G.D.H. & Bloemhof-Ruwaard, Jacqueline M. & van der Vorst, Jack G.A.J., 2017. "Closing loops in agricultural supply chains using multi-objective optimization: A case study of an industrial mushroom supply chain," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 409-420.
    15. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
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