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
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Cited by:
- 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.
- Imad El Harraki & Mohammad Zoynul Abedin & Amine Belhadi & Sachin Kamble & Karim Zkik & Mustapha Oudani, 2024.
"Data‐driven control and a prey–predator model for sourcing decisions in the low‐carbon intertwined supply chain,"
Business Strategy and the Environment, Wiley Blackwell, vol. 33(8), pages 9141-9160, December.
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