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A robust optimization model for cellular manufacturing system into supply chain management

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  • Aalaei, Amin
  • Davoudpour, Hamid

Abstract

In this paper, a new mathematical model is presented for a cellular manufacturing system into supply chain design with labor assignment. This paper considers important manufacturing features thoroughly such as multiple plant locations, multi-market allocations with production planning and various part mix. The proposed model aims at minimizing the total cost of holding, inter-cell material handling, external transportation, fixed cost for producing each part in each plant, machine and labor salaries. It is assumed that the demands of products are uncertainty in three scenarios: optimistic, pessimistic and normal. Also, a robust optimization approach is then developed to solve the proposed model and find the best solution. The robustness and performance of the proposed model are explained in terms of an industrial case from a typical equipment manufacturer. This case study provides the researchers and practitioners to better understand the importance of designing robust optimization and cell formation in the supply chain management from a practical point of view.

Suggested Citation

  • Aalaei, Amin & Davoudpour, Hamid, 2017. "A robust optimization model for cellular manufacturing system into supply chain management," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 667-679.
    • Handle: RePEc:eee:proeco:v:183:y:2017:i:pc:p:667-679
    DOI: 10.1016/j.ijpe.2016.01.014
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    Cited by:

    1. Alhawari, Omar I. & Süer, Gürsel A. & Bhutta, M. Khurrum S., 2021. "Operations performance considering demand coverage scenarios for individual products and products families in supply chains," International Journal of Production Economics, Elsevier, vol. 233(C).
    2. Songtao Zhang & Shuangshuang Li & Siqi Zhang & Min Zhang, 2017. "Decision of Lead-Time Compression and Stable Operation of Supply Chain," Complexity, Hindawi, vol. 2017, pages 1-11, November.
    3. Orji, Ifeyinwa Juliet & Liu, Shaoxuan, 2020. "A dynamic perspective on the key drivers of innovation-led lean approaches to achieve sustainability in manufacturing supply chain," International Journal of Production Economics, Elsevier, vol. 219(C), pages 480-496.
    4. Imen Zaabar & Vladimir Polotski & Léon Bérard & Boujemaa El-Ouaqaf & Yvan Beauregard & Marc Paquet, 2022. "A two-phase part family formation model to optimize resource planning: a case study in the electronics industry," Operational Research, Springer, vol. 22(4), pages 4441-4469, September.
    5. Margolis, Joshua T. & Sullivan, Kelly M. & Mason, Scott J. & Magagnotti, Mariah, 2018. "A multi-objective optimization model for designing resilient supply chain networks," International Journal of Production Economics, Elsevier, vol. 204(C), pages 174-185.
    6. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).

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