IDEAS home Printed from https://ideas.repec.org/a/ids/ijbpsc/v13y2022i2p139-166.html
   My bibliography  Save this article

Evaluation of supply chain routes based on control engineering and DEA considering traffic congestion and uncertainty

Author

Listed:
  • Ardavan Babaei
  • Majid Khedmati
  • Mohammad Reza Akbari Jokar

Abstract

In this paper, a mathematical model is proposed to assess the flow distribution based on the traffic criterion. In the mathematical model, the resilience and stability criteria are developed based on the concepts of control engineering and optimal control. The results show that the route stability is dependent on the traffic parameter. Then, considering several factors including stability, safety, resilience, risk-averse investment, the environment and noise, a decision-making model is presented to evaluate the performance of the flow distribution routes during crises. Goal programming and data-oriented modelling are used to solve the mathematical model. Data envelopment analysis (DEA) is used as the data-oriented model to evaluate the performance of scenarios under uncertainty. Furthermore, a decision-making methodology is proposed for ranking the routes. The results show that increasing beta can lead to lower desirability of a route. Finally, a managerial analysis is presented based on efficiency, risk, and PEST measures.

Suggested Citation

  • Ardavan Babaei & Majid Khedmati & Mohammad Reza Akbari Jokar, 2022. "Evaluation of supply chain routes based on control engineering and DEA considering traffic congestion and uncertainty," International Journal of Business Performance and Supply Chain Modelling, Inderscience Enterprises Ltd, vol. 13(2), pages 139-166.
    • Handle: RePEc:ids:ijbpsc:v:13:y:2022:i:2:p:139-166
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=124347
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ids:ijbpsc:v:13:y:2022:i:2:p:139-166. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=341 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.