IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03725131.html
   My bibliography  Save this paper

An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain

Author

Listed:
  • Hamza Bouzekri

    (G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, EMINES School of Industrial Management [UM6P] - UM6P - Université Mohammed VI Polytechnique [Ben Guerir])

  • Najat Bara

    (EMINES School of Industrial Management [UM6P] - UM6P - Université Mohammed VI Polytechnique [Ben Guerir])

  • Gülgün Alpan

    (G-SCOP_GCSP - Gestion et Conduite des Systèmes de Production - G-SCOP - Laboratoire des sciences pour la conception, l'optimisation et la production - CNRS - Centre National de la Recherche Scientifique - UGA - Université Grenoble Alpes - Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology - UGA - Université Grenoble Alpes, EMINES School of Industrial Management [UM6P] - UM6P - Université Mohammed VI Polytechnique [Ben Guerir])

  • Vincent Giard

    (LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique, EMINES School of Industrial Management [UM6P] - UM6P - Université Mohammed VI Polytechnique [Ben Guerir])

Abstract

Effective and efficient management of resources plays a crucial role in supply chains. This paper presents the bases of an integrated Decision Support System (DSS) for planning the operations of three successive echelons in the fertilizer part of a phosphate supply chain working in pull mode: production, vessel loading and storage where storage cannot constitute a decoupling point. Considering the whole perimeter of these planning operations within a monolithic optimization problem is much too huge to be solvable. Thus, the proposed DSS encapsulates an existing production scheduling model, an existing berth scheduling model, and a new model for the Storage Space Allocation Problem (SSAP). The latter provides a precise allocation of storage spaces for the fertilizers entering and leaving the hangars. Therefore, the proposed DSS aims to align production and storage decisions with vessel demands in a lean perspective, ensuring consistency in decision-making and keeping, if possible, the optimal solutions of production and port models. This approach is illustrated by several tests inspired by actual data provided by OCP Group on its operations at the Jorf Lasfar chemical platform in Morocco, but it is also valid for any other phosphate fertilizer producer that ships fertilizers in large batches from storage spaces directly linked to a fertilizer plant. This research yields several academic contributions in lean supply chain management and provides an original approach for modeling time in the SSAP.

Suggested Citation

  • Hamza Bouzekri & Najat Bara & Gülgün Alpan & Vincent Giard, 2022. "An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain," Post-Print hal-03725131, HAL.
  • Handle: RePEc:hal:journl:hal-03725131
    DOI: 10.1016/j.ijpe.2022.108561
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Mohamed Kriouich & Hicham Sarir, 2024. "Artificial Intelligence Application in Production Scheduling Problem Systematic Literature Review: Bibliometric Analysis, Research Trend, and Knowledge Taxonomy," SN Operations Research Forum, Springer, vol. 5(2), pages 1-24, June.

    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:hal:journl:hal-03725131. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.