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

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  • Bouzekri, Hamza
  • Bara, Najat
  • Alpan, Gülgün
  • Giard, Vincent

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

  • Bouzekri, Hamza & Bara, Najat & Alpan, Gülgün & Giard, Vincent, 2022. "An integrated Decision Support System for planning production, storage and bulk port operations in a fertilizer supply chain," International Journal of Production Economics, Elsevier, vol. 252(C).
    • Handle: RePEc:eee:proeco:v:252:y:2022:i:c:s0925527322001542
    DOI: 10.1016/j.ijpe.2022.108561
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