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Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach

Author

Listed:
  • Hashem Omrani

    (Urmia University of Technology)

  • Farzane Adabi

    (Urmia University of Technology)

  • Narges Adabi

    (Tabriz Islamic Art University)

Abstract

Designing a supply chain network (SCN) is an important issue for organizations in competitive markets. In this paper, a novel robust SCN that considers the efficiencies and costs simultaneously is proposed. In order to estimate the efficiency of the producers and distributors, data envelopment analysis (DEA) model is incorporated into SCN. Moreover, to handle the uncertainty in data, a scenario-based robust optimization approach is applied. The proposed model finds out the efficient location of producers and distributors and determines the amount of purchases from each supplier in uncertain conditions. To illustrate the application of the proposed model, a numerical example is solved and results are analyzed.

Suggested Citation

  • Hashem Omrani & Farzane Adabi & Narges Adabi, 2017. "Designing an efficient supply chain network with uncertain data: a robust optimization—data envelopment analysis approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(7), pages 816-828, July.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:7:d:10.1057_jors.2016.42
    DOI: 10.1057/jors.2016.42
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    Cited by:

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    2. Shahbazbegian, Vahid & Hosseini-Motlagh, Seyyed-Mahdi & Haeri, Abdorrahman, 2020. "Integrated forward/reverse logistics thin-film photovoltaic power plant supply chain network design with uncertain data," Applied Energy, Elsevier, vol. 277(C).
    3. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.
    4. Aneirson Francisco Silva & Fernando Augusto S. Marins & Erica Ximenes Dias, 2020. "Improving the discrimination power with a new multi-criteria data envelopment model," Annals of Operations Research, Springer, vol. 287(1), pages 127-159, April.
    5. Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar & Erfan Babaee Tirkolaee, 2022. "Performance Evaluation of Omni-Channel Distribution Network Configurations considering Green and Transparent Criteria under Uncertainty," Sustainability, MDPI, vol. 14(19), pages 1-15, October.
    6. Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar, 2023. "A new branch and efficiency algorithm for an optimal design of the supply chain network in view of resilience, inequity and traffic congestion," Annals of Operations Research, Springer, vol. 321(1), pages 49-78, February.

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