Publications
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Pricing-Driven Optimization of Lot-Sizing and Scheduling in Hybrid Manufacturing-Remanufacturing Systems
The transition towards sustainable production models has intensified interest in hybrid manufacturing and remanufacturing systems, which play a crucial role in the circular economy. These systems integrate new production with the refurbishment of used products, presenting unique operational challenges. This paper examines the integration of pricing, scheduling, and lot-sizing in modern industrial operations, with a […]
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Evaluating Ventilation Strategies for Energy- Efficient Classroom Design Using Open-Source CFD software (OpenFOAM®)
Given the urgent need for energy-efficient buildings and comfort-optimized ventilation due to rapid climate change, simulation tools provide a good, fast, and inexpensive approach to addressing these challenges. In this work, computational fluid dynamics is used in a classroom located in the north of France to assess HVAC performance of different ventilation scenarios, offering valuable […]
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Towards efficient program execution on edge-cloud computing platforms
This paper investigates techniques dedicated to the performance of edge-cloud infrastructures and identifies the challenges to address to maximize their efficiency. Unlike traditional cloud-only processing, edge-cloud platforms meet the stringent requirements of real-time applications via additional computing resources close to the data source. Yet, due to numerous performance factors, it is a complex task to […]
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Digital Twin–Driven Multi-Objective Layout Optimisation of Flexible Robotic Cells with NSGA-II
Robotic cells in modern factories must be laid out for efficiency, flexibility, and fast adaptation to shifting product mixes [1]. Cycle time and safety hinge on where workstations, robot bases, stock bins, and tools sit, yet finding a balanced layout is challenging because static choices alter dynamic behaviour: moving a fixture a few centimetres can […]
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Autoconsommation et stockage thermique de l’énergie solaire dans une habitation résidentielle
L’objectif de ce travail est de tester des méthodes de gestion et de stockage des énergies renouvelables produites au niveau d’une habitation individuelle. Un simulateur, fondé sur les modèles des équipements d’une habitation et des sources d’énergies renouvelables solaire qu’elle intègre, a été conçu à des fins de développement d’algorithmes d’optimisation pour l’amélioration de la […]
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JIT Organization Method for Sustainable and Integrated Production and Delivery Scheduling
This paper integrates sustainable production and delivery scheduling using a Just In Time approach to minimize delays and CO2 emissions in a job shop environment with hybrid vehicle fleets for the delivery. Beyond existing integrated production and delivery models, this work explicitly incorporates electric vehicle constraints, addressing energy consumption and charging requirements alongside scheduling decisions. […]
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Enhancing Industrial Process Optimization through Digital Twins
This paper explores the role of Digital Twins (DTs) in optimizing industrial processes, particularly in strategic sectors such as automotive, aerospace, and water treatment. With the growing need for companies to adapt to increased competition and technological advancements, DTs offer an innovative approach to process management. The study outlines the integration of real-time data analytics, […]
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Contribution à la caractérisation de l’affordance d’un environnement de travail industriel : une approche basée sur l’apprentissage profond combinant données réelles et synthétiques
Ce travail s’inscrit dans le cadre du projet “École De La Batterie”, dont l’un des objectifs concerne l’optimisation de la conception des postes de travail manuel dans le but d’améliorer leur ergonomie. Nos travaux s’inscrivent dans cette démarche et visent à caractériser l’affordance des éléments de ces environnements avec lesquels les opérateurs interagissent (outils, composants, […]
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GZSL-MoE: Apprentissage Généralisé Zéro-Shot basé sur le Mélange d’Experts pour la Segmentation Sémantique de Nuages de Points 3D Appliqué à un Jeu de Données d’Environnement de Collaboration Humain-Robot
Résumé L’approche d’apprentissage génératif zéro-shot ou zéro exemple de données (Generative Zero-Shot Learning, GZSL) a démontré un potentiel significatif dans les tâches de la segmentation sémantique de nuages de points 3D. GZSL approche exploite des modèles génératifs comme les GAN pour synthétiser des caractéristiques réalistes (caractéristiques réelles) des classes non vues. Cela permet au modèle […]
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From Individuals to Teams: A Conceptual Model for Group Behavior Integration in Industry 5.0
In Industry 5.0 environments, integrating human behavior models into scheduling and planning is essential. However, most research in this field focuses on individual modeling, overlooking the significant influence of group dynamics. Beyond isolated interactions, collective decisionmaking and team behaviors shape system performance, especially when deploying collaborative technologies such as Autonomous Intelligent Vehicles (AIVs) and smart […]
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Optimizing building envelope design across various French climates: A multi-objective approach using NSGA II and RMP method
Architects face a major challenge in designing buildings that enhance human comfort while minimizing energy consumption. To address this, the present work presents a novel multi-objective optimization approach, aiming to determine the optimal building envelope design. The developed approach focuses on minimizing energy consumption for both heating and cooling demand. Therefore, the methodology follows three […]
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Metaheuristic and Reinforcement Learning Techniques for Solving the Vehicle Routing Problem: A Literature Review
The Vehicle Routing Problem remains a pivotal challenge in combinatorial optimization, where the objective is to determine optimal routes for a fleet of vehicles serving geographically distributed customers under specific constraints. Over decades, a diverse spectrum of solution methodologies—spanning exact algorithms, heuristics, metaheuristics, and, more recently, machine learning—has emerged. This review critically examines the intersection […]
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