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A robust optimization model for agile and build-to-order supply chain planning under uncertainties

Author

Listed:
  • Morteza Lalmazloumian

    (Universiti Teknologi Malaysia)

  • Kuan Yew Wong

    (Universiti Teknologi Malaysia)

  • Kannan Govindan

    (University of Southern Denmark)

  • Devika Kannan

    (Aalborg University)

Abstract

Supply chain planning as one of the most important processes within the supply chain management concept, has a great impact on firms’ success or failure. This paper considers a supply chain planning problem of an agile manufacturing company operating in a build-to-order environment under various kinds of uncertainty. An integrated optimization approach of procurement, production and distribution costs associated with the supply chain members has been taken into account. A robust optimization scenario-based approach is used to absorb the influence of uncertain parameters and variables. The formulation is a robust optimization model with the objective of minimizing the expected total supply chain cost while maintaining customer service level. The developed multi-product, multi-period, multi-echelon robust mixed-integer linear programming model is then solved using the CPLEX optimization studio and guidance related to future areas of research is given.

Suggested Citation

  • Morteza Lalmazloumian & Kuan Yew Wong & Kannan Govindan & Devika Kannan, 2016. "A robust optimization model for agile and build-to-order supply chain planning under uncertainties," Annals of Operations Research, Springer, vol. 240(2), pages 435-470, May.
    • Handle: RePEc:spr:annopr:v:240:y:2016:i:2:d:10.1007_s10479-013-1421-5
    DOI: 10.1007/s10479-013-1421-5
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    6. Hêris Golpîra, 2017. "Robust bi-level optimization for an opportunistic supply chain network design problem in an uncertain and risky environment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 27(1), pages 21-41.
    7. Diabat, Ali & Jabbarzadeh, Armin & Khosrojerdi, Amir, 2019. "A perishable product supply chain network design problem with reliability and disruption considerations," International Journal of Production Economics, Elsevier, vol. 212(C), pages 125-138.
    8. Lin Chen & Ting Dong & Jin Peng & Dan Ralescu, 2023. "Uncertainty Analysis and Optimization Modeling with Application to Supply Chain Management: A Systematic Review," Mathematics, MDPI, vol. 11(11), pages 1-45, May.
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    12. 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.
    13. Shuihua Han & Yue Jiang & Ling Zhao & Stephen C. H. Leung & Zongwei Luo, 2020. "Weight reduction technology and supply chain network design under carbon emission restriction," Annals of Operations Research, Springer, vol. 290(1), pages 567-590, July.
    14. Sazvar, Z. & Mirzapour Al-e-hashem, S.M.J. & Govindan, K. & Bahli, B., 2016. "A novel mathematical model for a multi-period, multi-product optimal ordering problem considering expiry dates in a FEFO system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 93(C), pages 232-261.
    15. Tsan-Ming Choi & Kannan Govindan & Xiang Li & Yongjian Li, 2017. "Innovative supply chain optimization models with multiple uncertainty factors," Annals of Operations Research, Springer, vol. 257(1), pages 1-14, October.
    16. Diéssica Oliveira-Dias & José Moyano-Fuentes & Juan Manuel Maqueira-Marín, 2022. "Understanding the relationships between information technology and lean and agile supply chain strategies: a systematic literature review," Annals of Operations Research, Springer, vol. 312(2), pages 973-1005, May.
    17. Amirhosein Gholami & Nasim Nezamoddini & Mohammad T. Khasawneh, 2023. "Customized orders management in connected make-to-order supply chains," Operations Management Research, Springer, vol. 16(3), pages 1428-1443, September.

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