ELHAROUNI Fatine - Profil du chercheur

Informations du chercheur

Nom complet

ELHAROUNI Fatine

Grade

PA

Spécialité

Génie logistique

Thématique de recherche

Innovation collaborative; management projet; durabilité; qualité, pédagogie; softskills

Laboratoire

Laboratoire ingénierie des Systèmes et Applications

Établissement

Ecole Nationale des Sciences Appliquées de Marrakech

Ouvrages (0 au total)

Aucun ouvrage disponible.

Projets (0 au total)

Aucun projet disponible.

Publications (2 au total)

Assessing the Environmental Performance of the Food Industry Using Unsupervised Machine Learning

Auteur: Zineb Nafi, Rachid Benmoussa, Fatine Elharouni

Revue: IFIP Advances in Information and Communication Technology

Année: 2023

DOI: 10.1007/978-3-031-42532-5_9

AN APPROACH BASED ON MACHINE LEARNING AND DISCRETE EVENT SIMULATION FOR SUPPLY CHAIN OPTIMIZATION: THE CASE OF ON-STOCK CHAINS

Auteur: Zineb Nafi, Fatima Ezzahra Essaber, Fatine Elharouni, Benmoussa Rachid

Revue: 국제산업공학저널

Année: 2023

DOI: 10.23055/IJIETAP.2023.30.6.8613

Communications (5 au total)

Enhancing cosmetic Supply chain efficiency through demand forecasting using machine learning

Manifestation: The World Conference of AI-Powered Innovation and Inventive Design TFC-TRAI 2024

Date: 2024-11-06

Organisation: Cluj-Napoca, Romania

Designing sustainable products to satisfy customer needs and reduce environmental impact: A systematic review of the ANP-QFD-LCA approach to sustainable innovation.

Manifestation: The 7th edition of the International Conference on Industrial and Logistics Systems

Date: 2024-10-17

Organisation: Marrakech, Morocco

Digital twin for supply chain improvement: A case study of a building company

Manifestation: The 7th edition of the International Conference on Industrial and Logistics Systems

Date: 2024-10-17

Organisation: Marrakech, Morocco

L'entrepreneuriat, un atout majeur pour les profils scientifiques.

Manifestation: « 2ème atelier du jeune chercheur de L’académie d’innovation et l’entrepreneuriat»

Date: 2024-07-01

Organisation: IAE Sorbonne Paris

Assessing the Environmental Performance of the Food Industry Using Unsupervised Machine Learning

Manifestation: 23rd International TRIZ Future Conference, TFC 2023

Date: 2023-09-12

Organisation: Offenburg, Germany

Thèses (0 au total)

Aucune thèse disponible.