| Titre : | Developing a planning panel to forecast truck fleet size based on activity forecast |
| Auteurs : | Oussama Rahmani, Auteur ; Salah Eddine Adjabi, Auteur ; Iskander Zouaghi, Directeur de thèse |
| Type de document : | document électronique |
| Editeur : | [S.l.] : [s.n.], 2025 |
| Format : | 1 fichier PDF (4.4 Mo) / ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Génie Industriel.Management industriel : Alger, École Nationale Polytechnique : 2025 Bibliogr. p. 90 - 93 .- Annexe p. 94 - 107 |
| Langues : | Anglais |
| Index. décimale : | PI02525 |
| Tags : | Oil and Gas Services Supply Chain Optimization Mathematical Modeling Decision Support Tools Supply chain planning Planning adherence Dynamic Scheduling |
| Résumé : |
This thesis addresses inefficiencies in SLB Algeria’s domestic logistics by developing an integrated solution composed of a planning tool, an optimization model, and a performance dashboard. The planning panel, built in Excel VBA, improves visibility over job schedules, truck allocation, and material requirements. A mixed-integer linear programming model is implemented to retrospectively determine the minimum truck fleet needed to fulfill past demand while respecting operational constraints. A Power BI dashboard visualizes key performance indicators to assess efficiency and support decision-making.
Findings show that data-driven tools significantly improve planning accuracy, fleet utilization, and visibility. However, challenges remain regarding data integration, shipment consolidation logic, and tool scalability, indicating directions for future research. |
Exemplaires (1)
| Cote | Support | Localisation | Section | Disponibilité | Spécialité | Etat_Exemplaire |
|---|---|---|---|---|---|---|
| PI02525 | Ressources électroniques | Bibliothèque centrale | Projet Fin d'Etudes | Disponible | Management_Industriel | Téléchargeable |
