IDEAS home Printed from https://ideas.repec.org/a/spr/aodasc/v7y2020i2d10.1007_s40745-020-00268-y.html
   My bibliography  Save this article

A Mixed-Integer Programming Model to Configure a Post Supply Chain Network

Author

Listed:
  • Melika Parichehreh

    (Mazandaran University of Science and Technology)

  • Nikbakhsh Javadian

    (Mazandaran University of Science and Technology)

Abstract

Points of distribution, sales or service are important elements of the supply chain. These are the final elements which are responsible for proper functioning of the whole cargo distribution process. Proper location of these points in the transport network is essential to ensure the effectiveness and reliability of the supply chain. The location of these points is very important also from the consumer’s point of view. In this paper, a mathematical model is proposed to design of a post supply chain network to minimize transportation cost, facilities location cost and holding cost. The proposed supply chain network consists of four echelons: supplier, post office, distribution center, and recipient. The bold point of this study is as regards the post supply chain is examined, the demand of the recipient’s point determines in supplier point not in delivery point. Finally, the proposed model is solved by LINGO 17 software and the results are analyzed.

Suggested Citation

  • Melika Parichehreh & Nikbakhsh Javadian, 2020. "A Mixed-Integer Programming Model to Configure a Post Supply Chain Network," Annals of Data Science, Springer, vol. 7(2), pages 281-290, June.
    • Handle: RePEc:spr:aodasc:v:7:y:2020:i:2:d:10.1007_s40745-020-00268-y
    DOI: 10.1007/s40745-020-00268-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s40745-020-00268-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s40745-020-00268-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    References listed on IDEAS

    as
    1. Fahimeh Aliakbari Nouri & Mohsen Shafiei Nikabadi & Laya Olfat, 2019. "The Role of Supply Chain Features in the Effectiveness of Sustainability Practices in the Service Supply Chain: Application of Fuzzy Rule-Based System," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(03), pages 867-899, May.
    2. Sun, Li & Zhao, Lindu & Hou, Jing, 2015. "Optimization of postal express line network under mixed driving pattern of trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 147-169.
    3. Qian Qian & Yang Yang & Zong-Fang Zhou, 2019. "Research on Trade Credit Spreading and Credit Risk within the Supply Chain," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 389-411, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gunpinar, Serkan & Centeno, Grisselle, 2016. "An integer programming approach to the bloodmobile routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 94-115.
    2. Paweł DROŹDZIEL & Monika WIŃSKA & Radovan MADLEŇÁK & Paweł SZUMSKI, 2017. "Optimization Of The Position Of The Local Distribution Centre Of The Regional Post Logistics Network," Transport Problems, Silesian University of Technology, Faculty of Transport, vol. 12(3), pages 43-50, September.
    3. Shaohua Cui & Hui Zhao & Cuiping Zhang, 2018. "Multiple Types of Plug-In Charging Facilities’ Location-Routing Problem with Time Windows for Mobile Charging Vehicles," Sustainability, MDPI, vol. 10(8), pages 1-26, August.
    4. Hamzeh Aghababayi & Mohsen Shafiei Nikabadi, 2021. "An Integrated Fuzzy Model for Selecting Resilient Suppliers in Electronics Industry of Iran," Logistics, MDPI, vol. 5(4), pages 1-22, October.
    5. Lei Tang & Jingchi Jia & Zongtao Duan & Jingyu Ma & Xin Wang & Weiwei Kong, 2020. "Tracking and climbing behavior recognition of heavy-duty trucks on roadways," International Journal of Distributed Sensor Networks, , vol. 16(2), pages 15501477209, February.

    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:spr:aodasc:v:7:y:2020:i:2:d:10.1007_s40745-020-00268-y. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.