IDEAS home Printed from https://ideas.repec.org/a/ids/ijlsma/v35y2020i4p436-452.html
   My bibliography  Save this article

Green supply chain network design considering inventory-location-routing problem: a fuzzy solution approach

Author

Listed:
  • Sobhgol Gholipour
  • Amir Ashoftehfard
  • Hassan Mina

Abstract

The growing rate of population and technological advancement have led to an increase in natural resource consumption, which has caused irreparable damage to the environment. The implementation of green supply chain management is one of the most effective ways to deal with environmental degradation. Therefore, in this paper, a bi-objective mixed integer linear programming model is developed to design a green supply chain network. In the proposed model, the possibility of customer storage, being faced with shortage, locating of distribution centres, green vehicle routing problem, split delivery, multi-depot vehicle routing problem (VRP), capacitated VRP, and uncertainty in demands will be considered. The aim of the proposed model is to minimise the total cost and total shortages simultaneously and, therefore, a fuzzy solution approach is applied for this purpose. The results of implementing this model in a production chain of automotive parts in Iran indicate the exact and efficient performance of the proposed model.

Suggested Citation

  • Sobhgol Gholipour & Amir Ashoftehfard & Hassan Mina, 2020. "Green supply chain network design considering inventory-location-routing problem: a fuzzy solution approach," International Journal of Logistics Systems and Management, Inderscience Enterprises Ltd, vol. 35(4), pages 436-452.
    • Handle: RePEc:ids:ijlsma:v:35:y:2020:i:4:p:436-452
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=106272
    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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. M. Tadaros & A. Migdalas, 2022. "Bi- and multi-objective location routing problems: classification and literature review," Operational Research, Springer, vol. 22(5), pages 4641-4683, November.
    2. Katherinne Salas-Navarro & Paula Serrano-Pájaro & Holman Ospina-Mateus & Ronald Zamora-Musa, 2022. "Inventory Models in a Sustainable Supply Chain: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(10), pages 1-21, May.
    3. Lihua Liu & Lai Soon Lee & Hsin-Vonn Seow & Chuei Yee Chen, 2022. "Logistics Center Location-Inventory-Routing Problem Optimization: A Systematic Review Using PRISMA Method," Sustainability, MDPI, vol. 14(23), pages 1-39, November.

    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:ijlsma:v:35:y:2020:i:4:p:436-452. 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=134 .

    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.